diff --git a/analysis/src/benchmark_analysis/cli.py b/analysis/src/benchmark_analysis/cli.py
index 4875b605..56df8e4a 100644
--- a/analysis/src/benchmark_analysis/cli.py
+++ b/analysis/src/benchmark_analysis/cli.py
@@ -675,70 +675,40 @@ def main():
         recs, skipped = parse_csv_file(path, language_hint=lang)
         total_loaded += len(recs)
         if recs:
-            # One sanitize pass → same population for tables and latency distributions.
-            clean, meta = prepare_analysis_records(
+            # Multi-policy stats for dashboard outlier research; default policy
+            # still feeds markdown tables / latency distributions.
+            from .stats import (
+                DEFAULT_FILTER_POLICY,
+                build_stats_export_payload,
+                compute_statistics_multi_policy,
+                config_for_filter_policy,
+            )
+
+            by_policy = compute_statistics_multi_policy(
                 recs, config=stats_cfg, language_hint=lang
             )
+            default_pid = DEFAULT_FILTER_POLICY
+            if default_pid not in by_policy:
+                default_pid = next(iter(by_policy), DEFAULT_FILTER_POLICY)
+            st = by_policy.get(default_pid) or {}
+            all_stats.update(st)
+
+            # Sanitize once under default policy for shared plot population
+            default_cfg = config_for_filter_policy(stats_cfg, default_pid)
+            clean, _meta = prepare_analysis_records(
+                recs, config=default_cfg, language_hint=lang
+            )
             all_records[lang] = clean
             total_sanitized += len(clean)
-            st = compute_statistics(
-                clean,
-                config=stats_cfg,
-                language_hint=lang,
-                pre_sanitized=True,
-                group_meta=meta,
-            )
-            all_stats.update(st)
-            
-            # Export to machine-readable JSON: reports/stats_<lang>_latest.json
+
+            # Export machine-readable JSON with all filter policies
             try:
                 import json
-                import datetime
+
                 os.makedirs(str(reports_root), exist_ok=True)
-                groups_list = []
-                for entry in st.values():
-                    # Strip private helper keys (like _times_total_filtered)
-                    clean_entry = {k: v for k, v in entry.items() if not k.startswith("_")}
-                    groups_list.append(clean_entry)
-                
-                # Dynamic Pareto front computation
-                pareto_front = []
-                workloads = {}
-                for g in groups_list:
-                    wkey = (g["test_data"], g["mode"])
-                    workloads.setdefault(wkey, []).append(g)
-                for wkey, items in workloads.items():
-                    for item in items:
-                        dominated = False
-                        for other in items:
-                            if other == item:
-                                continue
-                            if ((other["avg_time_total_ns"] <= item["avg_time_total_ns"] and other["median_size_bytes"] < item["median_size_bytes"]) or
-                                (other["avg_time_total_ns"] < item["avg_time_total_ns"] and other["median_size_bytes"] <= item["median_size_bytes"])):
-                                dominated = True
-                                break
-                        if not dominated:
-                            pareto_front.append({
-                                "serializer": item["serializer"],
-                                "test_data": item["test_data"],
-                                "mode": item["mode"],
-                                "time": item["avg_time_total_ns"],
-                                "size": item["median_size_bytes"]
-                            })
-
-                export_data = {
-                    "schema_version": "2.0",
-                    "generated": datetime.datetime.now().isoformat(),
-                    "language": lang,
-                    "questions": {
-                        "Q1": "How fast?",
-                        "Q2": "How compact?",
-                        "Q3": "How stable?",
-                        "Q4": "Under which workloads does it win?"
-                    },
-                    "groups": groups_list,
-                    "pareto_front": pareto_front
-                }
+                export_data = build_stats_export_payload(
+                    by_policy, language=lang, default_policy=default_pid
+                )
                 latest_json_path = reports_root / f"stats_{lang}_latest.json"
                 with open(latest_json_path, "w", encoding="utf-8") as f:
                     json.dump(export_data, f, indent=2)
@@ -747,7 +717,8 @@ def main():
 
             print(
                 f"Loaded {len(recs)} {lang} records from {os.path.basename(path)} "
-                f"-> {len(clean)} after sanitize, {len(st)} stat groups "
+                f"-> {len(clean)} after sanitize ({default_pid}), {len(st)} stat groups "
+                f"× {len(by_policy)} filter policies "
                 f"(parse-skipped {skipped})"
             )
         else:
diff --git a/analysis/src/benchmark_analysis/stats.py b/analysis/src/benchmark_analysis/stats.py
index ce4e6f03..87a92e22 100644
--- a/analysis/src/benchmark_analysis/stats.py
+++ b/analysis/src/benchmark_analysis/stats.py
@@ -21,6 +21,63 @@
 # Config helpers (optional YAML; safe defaults if PyYAML / file missing)
 # ---------------------------------------------------------------------------
 
+# Named filter policies exported for dashboard outlier research.
+# Keys are stable API ids; criteria are fixed (not taken from YAML outlier_method).
+FILTER_POLICY_IDS: Tuple[str, ...] = (
+    "all",
+    "iqr_1.5",
+    "iqr_3",
+    "winsorize_5_95",
+)
+DEFAULT_FILTER_POLICY = "iqr_1.5"
+
+FILTER_POLICY_SPECS: Dict[str, Dict[str, Any]] = {
+    "all": {
+        "label": "All trials (post-warmup)",
+        "description": (
+            "Every measured repetition after warmup exclusion. "
+            "No IQR drop and no winsorization — includes GC and scheduler tails."
+        ),
+        "outlier_method": "none",
+        "iqr_k": None,
+        "winsorize_percentiles": None,
+        "paired": None,
+    },
+    "iqr_1.5": {
+        "label": "IQR k=1.5 (strict / default)",
+        "description": (
+            "Tukey fences with k=1.5 on serialize, deserialize, and total; "
+            "a repetition is dropped if it is an outlier on any of the three (paired)."
+        ),
+        "outlier_method": "iqr",
+        "iqr_k": 1.5,
+        "winsorize_percentiles": None,
+        "paired": True,
+    },
+    "iqr_3": {
+        "label": "IQR k=3 (loose)",
+        "description": (
+            "Same paired IQR rule as iqr_1.5 but with k=3 so only extreme stalls "
+            "are removed; bulk tail mass is retained."
+        ),
+        "outlier_method": "iqr",
+        "iqr_k": 3.0,
+        "winsorize_percentiles": None,
+        "paired": True,
+    },
+    "winsorize_5_95": {
+        "label": "Winsorize 5–95%",
+        "description": (
+            "Clip each of ser/deser/total independently at the 5th and 95th "
+            "percentiles; sample size is unchanged (no rows dropped)."
+        ),
+        "outlier_method": "winsorize",
+        "iqr_k": None,
+        "winsorize_percentiles": [5.0, 95.0],
+        "paired": False,
+    },
+}
+
 _DEFAULT_STATS_CFG: Dict[str, Any] = {
     "exclude_warmup": True,
     "outlier_method": "iqr",
@@ -422,8 +479,19 @@ def _scale_for(lang: str) -> float:
 
     # Bucket non-warmup rows by analysis group key
     buckets: Dict[Tuple, List[Dict]] = defaultdict(list)
-    group_meta: Dict[Tuple, Dict[str, int]] = defaultdict(
-        lambda: {"warmup_skipped": 0, "outliers_removed": 0, "runs_raw": 0}
+    group_meta: Dict[Tuple, Dict[str, Any]] = defaultdict(
+        lambda: {
+            "warmup_skipped": 0,
+            "outliers_removed": 0,
+            "values_clipped": 0,
+            "runs_raw": 0,
+            "fence_total_low_ns": None,
+            "fence_total_high_ns": None,
+            "fence_ser_low_ns": None,
+            "fence_ser_high_ns": None,
+            "fence_deser_low_ns": None,
+            "fence_deser_high_ns": None,
+        }
     )
 
     for r in records:
@@ -454,11 +522,37 @@ def _scale_for(lang: str) -> float:
         deser = [float(x["TimeDeser"]) for x in recs]
         total = [float(x["TimeSerAndDeser"]) for x in recs]
 
+        if outlier_method == "iqr" and len(recs) >= min_out:
+            for series, lo_k, hi_k in (
+                (ser, "fence_ser_low_ns", "fence_ser_high_ns"),
+                (deser, "fence_deser_low_ns", "fence_deser_high_ns"),
+                (total, "fence_total_low_ns", "fence_total_high_ns"),
+            ):
+                lo, hi = _iqr_fence_bounds(series, iqr_k=iqr_k, min_samples=min_out)
+                group_meta[key][lo_k] = lo
+                group_meta[key][hi_k] = hi
+
         if outlier_method == "winsorize" and len(recs) >= min_out:
             s_f, d_f, t_f, rem = filter_outliers_paired(
                 ser, deser, total, method="winsorize", iqr_k=iqr_k, min_samples=min_out
             )
-            group_meta[key]["outliers_removed"] = rem
+            group_meta[key]["outliers_removed"] = rem  # always 0 for winsorize
+            clipped_rows = sum(
+                1
+                for i in range(len(ser))
+                if ser[i] != s_f[i] or deser[i] != d_f[i] or total[i] != t_f[i]
+            )
+            group_meta[key]["values_clipped"] = int(clipped_rows)
+            # Store clip bounds from total (and ser/deser) for provenance
+            for series, lo_k, hi_k in (
+                (ser, "fence_ser_low_ns", "fence_ser_high_ns"),
+                (deser, "fence_deser_low_ns", "fence_deser_high_ns"),
+                (total, "fence_total_low_ns", "fence_total_high_ns"),
+            ):
+                arr = np.asarray(series, dtype=float)
+                lo, hi = np.percentile(arr, [5, 95])
+                group_meta[key][lo_k] = float(lo)
+                group_meta[key][hi_k] = float(hi)
             for rec, ts, td, tt in zip(recs, s_f, d_f, t_f):
                 out = dict(rec)
                 out["TimeSer"] = ts
@@ -472,6 +566,7 @@ def _scale_for(lang: str) -> float:
         )
         rem = int((~mask).sum())
         group_meta[key]["outliers_removed"] = rem
+        group_meta[key]["values_clipped"] = 0
         for rec, keep in zip(recs, mask):
             if keep:
                 sanitized.append(rec)
@@ -479,6 +574,24 @@ def _scale_for(lang: str) -> float:
     return sanitized, dict(group_meta)
 
 
+def _iqr_fence_bounds(
+    values: Sequence[float],
+    iqr_k: float = 1.5,
+    min_samples: int = 10,
+) -> Tuple[Optional[float], Optional[float]]:
+    """Return (lower, upper) Tukey fences, or (None, None) if not applicable."""
+    arr = np.asarray(values, dtype=float)
+    n = len(arr)
+    if n < min_samples:
+        return None, None
+    q1 = float(np.percentile(arr, 25))
+    q3 = float(np.percentile(arr, 75))
+    iqr = q3 - q1
+    if iqr == 0:
+        return None, None
+    return q1 - iqr_k * iqr, q3 + iqr_k * iqr
+
+
 # ---------------------------------------------------------------------------
 # Bootstrap CI
 # ---------------------------------------------------------------------------
@@ -849,6 +962,7 @@ def compute_statistics(
         times_total = data["times_total"]
         m = meta.get(key) or {}
         rem_t = int(m.get("outliers_removed", 0))
+        values_clipped = int(m.get("values_clipped", 0))
         warmup_skipped = int(m.get("warmup_skipped", 0))
         runs_raw = int(m.get("runs_raw", len(times_total) + warmup_skipped + rem_t))
         total_outliers += rem_t
@@ -884,6 +998,7 @@ def compute_statistics(
             "runs_raw": runs_raw,
             "warmup_skipped": warmup_skipped,
             "outliers_removed": rem_t,
+            "values_clipped": values_clipped,
             # Extended scientific metrics
             **ser_stats,
             **deser_stats,
@@ -893,6 +1008,12 @@ def compute_statistics(
             # Retain filtered series for effect-size / A-B (not serialized by default consumers)
             "_times_total_filtered": times_total,
         }
+        entry["filter"] = _build_filter_block(
+            policy_id=m.get("filter_policy"),
+            cfg=cfg,
+            entry=entry,
+            meta=m,
+        )
         # B-6: majority StreamMode label for this group (stream I/O rows)
         sms = [s for s in (data.get("stream_modes") or []) if s]
         if sms:
@@ -920,6 +1041,317 @@ def compute_statistics(
     return results
 
 
+def config_for_filter_policy(
+    base_config: Optional[Dict[str, Any]],
+    policy_id: str,
+) -> Dict[str, Any]:
+    """Return a stats config with outlier settings forced to a named policy."""
+    if policy_id not in FILTER_POLICY_SPECS:
+        raise ValueError(
+            f"Unknown filter policy {policy_id!r}; expected one of {list(FILTER_POLICY_SPECS)}"
+        )
+    cfg = dict(base_config or load_stats_config())
+    spec = FILTER_POLICY_SPECS[policy_id]
+    cfg["outlier_method"] = spec["outlier_method"]
+    if spec.get("iqr_k") is not None:
+        cfg["iqr_k"] = float(spec["iqr_k"])
+    return cfg
+
+
+def filter_policy_catalog() -> Dict[str, Dict[str, Any]]:
+    """Public catalog of filter policies (no internal-only fields)."""
+    out: Dict[str, Dict[str, Any]] = {}
+    for pid, spec in FILTER_POLICY_SPECS.items():
+        out[pid] = {
+            "id": pid,
+            "label": spec["label"],
+            "description": spec["description"],
+            "outlier_method": spec["outlier_method"],
+            "iqr_k": spec.get("iqr_k"),
+            "winsorize_percentiles": spec.get("winsorize_percentiles"),
+            "paired": spec.get("paired"),
+            "min_samples_for_outlier_filter": _DEFAULT_STATS_CFG[
+                "min_samples_for_outlier_filter"
+            ],
+            "exclude_warmup": _DEFAULT_STATS_CFG["exclude_warmup"],
+        }
+    return out
+
+
+def _infer_policy_id(cfg: Dict[str, Any]) -> Optional[str]:
+    method = str(cfg.get("outlier_method") or "iqr").lower()
+    if method == "none":
+        return "all"
+    if method == "winsorize":
+        return "winsorize_5_95"
+    if method == "iqr":
+        k = float(cfg.get("iqr_k", 1.5))
+        if abs(k - 1.5) < 1e-9:
+            return "iqr_1.5"
+        if abs(k - 3.0) < 1e-9:
+            return "iqr_3"
+    return None
+
+
+# Group identity fields shared across filter-policy variants (schema 2.2).
+_EXPORT_IDENTITY_KEYS: Tuple[str, ...] = (
+    "serializer",
+    "test_data",
+    "type_config_hash",
+    "data_type_instance_count",
+    "mode",
+    "language",
+    "serializer_version",
+)
+
+
+def _build_filter_block(
+    policy_id: Optional[str],
+    cfg: Dict[str, Any],
+    entry: Dict[str, Any],
+    meta: Dict[str, Any],
+    *,
+    include_catalog_text: bool = False,
+) -> Dict[str, Any]:
+    """Provenance block describing how this group's sample was filtered.
+
+    By default omits ``label`` / ``description`` (schema 2.2 recommendation D):
+    those live once in ``filter_policies``. Pass ``include_catalog_text=True``
+    for in-memory full blocks (e.g. multi_policy before export slim).
+    """
+    pid = policy_id or _infer_policy_id(cfg)
+    spec = FILTER_POLICY_SPECS.get(pid or "", {})
+    method = str(cfg.get("outlier_method") or spec.get("outlier_method") or "iqr")
+    iqr_k = cfg.get("iqr_k") if method == "iqr" else spec.get("iqr_k")
+    winsor = (
+        list(spec.get("winsorize_percentiles") or [5.0, 95.0])
+        if method == "winsorize"
+        else None
+    )
+    paired = spec.get("paired")
+    if paired is None and method == "iqr":
+        paired = True
+    if method == "winsorize":
+        paired = False
+    if method == "none":
+        paired = None
+
+    block: Dict[str, Any] = {
+        "policy": pid,
+        "method": method,
+        "iqr_k": float(iqr_k) if iqr_k is not None and method == "iqr" else None,
+        "winsorize_percentiles": winsor,
+        "paired": paired,
+        "exclude_warmup": bool(cfg.get("exclude_warmup", True)),
+        "min_samples_for_outlier_filter": int(
+            cfg.get("min_samples_for_outlier_filter", 10)
+        ),
+        "runs_raw": int(entry.get("runs_raw") or 0),
+        "warmup_skipped": int(entry.get("warmup_skipped") or 0),
+        "runs_kept": int(entry.get("runs") or 0),
+        "outliers_removed": int(entry.get("outliers_removed") or 0),
+        "values_clipped": int(entry.get("values_clipped") or 0),
+        "fence_total_low_ns": meta.get("fence_total_low_ns"),
+        "fence_total_high_ns": meta.get("fence_total_high_ns"),
+        "fence_ser_low_ns": meta.get("fence_ser_low_ns"),
+        "fence_ser_high_ns": meta.get("fence_ser_high_ns"),
+        "fence_deser_low_ns": meta.get("fence_deser_low_ns"),
+        "fence_deser_high_ns": meta.get("fence_deser_high_ns"),
+    }
+    if include_catalog_text:
+        block["label"] = spec.get("label") or method
+        block["description"] = spec.get("description")
+    return block
+
+
+def slim_filter_block(filter_block: Optional[Dict[str, Any]]) -> Optional[Dict[str, Any]]:
+    """Drop catalog-duplicated text from a per-group filter block (rec D)."""
+    if not filter_block:
+        return filter_block
+    return {
+        k: v
+        for k, v in filter_block.items()
+        if k not in ("label", "description")
+    }
+
+
+def public_stats_entry(entry: Dict[str, Any]) -> Dict[str, Any]:
+    """Drop private underscore keys for JSON export."""
+    return {k: v for k, v in entry.items() if not str(k).startswith("_")}
+
+
+def compute_pareto_front(groups: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
+    """Classical 2D Pareto: minimize avg_time_total_ns and median_size_bytes."""
+    front: List[Dict[str, Any]] = []
+    workloads: Dict[Tuple[Any, Any], List[Dict[str, Any]]] = {}
+    for g in groups:
+        wkey = (g.get("test_data"), g.get("mode"))
+        workloads.setdefault(wkey, []).append(g)
+    for items in workloads.values():
+        for item in items:
+            t = item.get("avg_time_total_ns")
+            s = item.get("median_size_bytes")
+            if t is None or s is None:
+                continue
+            dominated = False
+            for other in items:
+                if other is item:
+                    continue
+                ot = other.get("avg_time_total_ns")
+                os_ = other.get("median_size_bytes")
+                if ot is None or os_ is None:
+                    continue
+                if (ot <= t and os_ < s) or (ot < t and os_ <= s):
+                    dominated = True
+                    break
+            if not dominated:
+                front.append(
+                    {
+                        "serializer": item.get("serializer"),
+                        "test_data": item.get("test_data"),
+                        "mode": item.get("mode"),
+                        "time": t,
+                        "size": s,
+                        "filter_policy": (item.get("filter") or {}).get("policy"),
+                    }
+                )
+    return front
+
+
+def compute_statistics_multi_policy(
+    records: List[Dict],
+    config: Optional[Dict[str, Any]] = None,
+    language_hint: Optional[str] = None,
+    policies: Optional[Sequence[str]] = None,
+) -> Dict[str, Dict]:
+    """Compute full stats under each named filter policy.
+
+    Returns ``{policy_id: {group_key: entry}}``. Each entry includes a
+    ``filter`` provenance block. Effect sizes are recomputed per policy
+    (comparisons only among groups sharing that sample set).
+    """
+    base = config or load_stats_config()
+    policy_ids = list(policies) if policies is not None else list(FILTER_POLICY_IDS)
+    result: Dict[str, Dict] = {}
+    for pid in policy_ids:
+        cfg = config_for_filter_policy(base, pid)
+        clean, meta = prepare_analysis_records(
+            records, config=cfg, language_hint=language_hint
+        )
+        # Tag meta so entries get the stable policy id
+        for key in meta:
+            meta[key]["filter_policy"] = pid
+        stats = compute_statistics(
+            clean,
+            config=cfg,
+            language_hint=language_hint,
+            pre_sanitized=True,
+            group_meta=meta,
+        )
+        # Ensure policy id is set even for empty-meta edge cases
+        for entry in stats.values():
+            fb = entry.get("filter") or {}
+            fb["policy"] = pid
+            entry["filter"] = slim_filter_block(fb)
+        result[pid] = stats
+    return result
+
+
+def build_stats_export_payload(
+    by_policy: Dict[str, Dict],
+    language: str,
+    default_policy: str = DEFAULT_FILTER_POLICY,
+    generated: Optional[str] = None,
+) -> Dict[str, Any]:
+    """Assemble schema **2.2** compact multi-policy stats export.
+
+    Size reductions vs 2.1:
+    - **B** no duplicate flat ``groups`` list equal to default policy
+    - **C** identity once + ``variants`` per policy (no ``groups_by_policy`` blow-up)
+    - **D** filter blocks omit catalog ``label``/``description``
+    - Pareto fronts omitted (dashboard recomputes from metrics)
+
+    Dashboard expands variants client-side. Prefer publishing as
+    ``stats_<lang>_latest.json.gz`` (recommendation A).
+    """
+    import datetime as _dt
+
+    if default_policy not in by_policy and by_policy:
+        default_policy = next(iter(by_policy))
+
+    # Preserve policy order: FILTER_POLICY_IDS first, then any extras
+    policy_order: List[str] = [p for p in FILTER_POLICY_IDS if p in by_policy]
+    for p in by_policy:
+        if p not in policy_order:
+            policy_order.append(p)
+
+    # Union of group keys across policies (stable sort for determinism)
+    all_keys: List[Any] = sorted(
+        {k for stats in by_policy.values() for k in stats.keys()},
+        key=lambda k: tuple(str(x) for x in (k if isinstance(k, tuple) else (k,))),
+    )
+
+    catalog = filter_policy_catalog()
+    slim_groups: List[Dict[str, Any]] = []
+
+    for key in all_keys:
+        # Identity from first available policy entry
+        base_pub: Optional[Dict[str, Any]] = None
+        for pid in policy_order:
+            if key in by_policy[pid]:
+                base_pub = public_stats_entry(by_policy[pid][key])
+                break
+        if not base_pub:
+            continue
+
+        identity: Dict[str, Any] = {
+            k: base_pub.get(k) for k in _EXPORT_IDENTITY_KEYS
+        }
+        if base_pub.get("StreamMode") is not None:
+            identity["StreamMode"] = base_pub.get("StreamMode")
+
+        variants: Dict[str, Dict[str, Any]] = {}
+        for pid in policy_order:
+            if key not in by_policy[pid]:
+                continue
+            pub = public_stats_entry(by_policy[pid][key])
+            metrics = {
+                k: v
+                for k, v in pub.items()
+                if k not in _EXPORT_IDENTITY_KEYS and k != "StreamMode"
+            }
+            if isinstance(metrics.get("filter"), dict):
+                metrics["filter"] = slim_filter_block(metrics["filter"])
+            variants[pid] = metrics
+
+            # Refresh catalog min_samples / warmup from first seen filter
+            fb = metrics.get("filter") or {}
+            if pid in catalog:
+                if fb.get("min_samples_for_outlier_filter") is not None:
+                    catalog[pid]["min_samples_for_outlier_filter"] = fb[
+                        "min_samples_for_outlier_filter"
+                    ]
+                if fb.get("exclude_warmup") is not None:
+                    catalog[pid]["exclude_warmup"] = fb["exclude_warmup"]
+
+        slim_groups.append({**identity, "variants": variants})
+
+    return {
+        "schema_version": "2.2",
+        "generated": generated or _dt.datetime.now().isoformat(),
+        "language": language,
+        "default_filter_policy": default_policy,
+        "filter_policies": catalog,
+        "questions": {
+            "Q1": "How fast?",
+            "Q2": "How compact?",
+            "Q3": "How stable?",
+            "Q4": "Under which workloads does it win?",
+        },
+        "groups": slim_groups,
+    }
+
+
 def _attach_effect_sizes(results: Dict, cfg: Dict[str, Any]) -> None:
     """Attach effect size + MWU vs fastest in same (lang, data, instance, mode) group.
 
diff --git a/analysis/tests/test_stats.py b/analysis/tests/test_stats.py
index bb6288a4..b21cfb0d 100644
--- a/analysis/tests/test_stats.py
+++ b/analysis/tests/test_stats.py
@@ -13,12 +13,16 @@
 sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "src"))
 
 from benchmark_analysis.stats import (
+    DEFAULT_FILTER_POLICY,
+    FILTER_POLICY_IDS,
     _derive_seed,
     _filter_outliers,
     bootstrap_ci,
+    build_stats_export_payload,
     cliffs_delta,
     cliffs_delta_label,
     compute_statistics,
+    compute_statistics_multi_policy,
     filter_outliers_paired,
     hedges_g,
     holm_correction,
@@ -398,6 +402,77 @@ def test_paired_n_equal_across_metrics_after_stats():
     assert entry["runs"] < entry["runs_raw"] - entry["warmup_skipped"] or entry["outliers_removed"] >= 0
 
 
+def test_multi_policy_all_four_and_export_payload():
+    """Four named policies differ on a spiked series; export is schema 2.1."""
+    recs = _make_records(30)
+    # Strong total spike on last measured rep → IQR k=1.5 drops; k=3 may keep
+    recs[-1]["TimeSer"] = 50_000_000.0
+    recs[-1]["TimeDeser"] = 50_000_000.0
+    recs[-1]["TimeSerAndDeser"] = 100_000_000.0
+
+    cfg = {
+        "exclude_warmup": True,
+        "bootstrap": {"enabled": False},
+        "effect_sizes": {"enabled": False},
+        "hypothesis_tests": {"enabled": False},
+        "min_samples_for_outlier_filter": 10,
+    }
+    by_policy = compute_statistics_multi_policy(recs, config=cfg, language_hint="python")
+    assert list(by_policy.keys()) == list(FILTER_POLICY_IDS)
+
+    all_e = next(iter(by_policy["all"].values()))
+    iqr15 = next(iter(by_policy["iqr_1.5"].values()))
+    iqr3 = next(iter(by_policy["iqr_3"].values()))
+    win = next(iter(by_policy["winsorize_5_95"].values()))
+
+    # all keeps every post-warmup rep
+    assert all_e["outliers_removed"] == 0
+    assert all_e["runs"] == all_e["runs_raw"] - all_e["warmup_skipped"]
+    assert all_e["filter"]["policy"] == "all"
+    assert all_e["filter"]["method"] == "none"
+
+    # strict IQR removes the spike; mean is lower than unfiltered
+    assert iqr15["outliers_removed"] >= 1
+    assert iqr15["runs"] < all_e["runs"]
+    assert iqr15["avg_time_total_ns"] < all_e["avg_time_total_ns"]
+    assert iqr15["filter"]["policy"] == "iqr_1.5"
+    assert iqr15["filter"]["iqr_k"] == 1.5
+    assert iqr15["filter"]["fence_total_high_ns"] is not None
+
+    # loose IQR removes fewer or equal vs strict
+    assert iqr3["outliers_removed"] <= iqr15["outliers_removed"]
+    assert iqr3["filter"]["iqr_k"] == 3.0
+
+    # winsorize keeps n, may clip
+    assert win["runs"] == all_e["runs"]
+    assert win["outliers_removed"] == 0
+    assert win["values_clipped"] >= 1
+    assert win["filter"]["method"] == "winsorize"
+    assert win["filter"]["winsorize_percentiles"] == [5.0, 95.0]
+    # clipped mean should not be as extreme as raw all
+    assert win["avg_time_total_ns"] < all_e["avg_time_total_ns"]
+
+    payload = build_stats_export_payload(by_policy, language="python")
+    assert payload["schema_version"] == "2.2"
+    assert payload["default_filter_policy"] == DEFAULT_FILTER_POLICY
+    assert "groups_by_policy" not in payload  # B: no duplicate multi-list
+    assert "pareto_by_policy" not in payload  # client recomputes
+    assert "filter_policies" in payload and "iqr_1.5" in payload["filter_policies"]
+    # C: identity once + variants
+    sample = payload["groups"][0]
+    assert "variants" in sample
+    assert set(sample["variants"]) == set(FILTER_POLICY_IDS)
+    assert "serializer" in sample and "avg_ops_per_sec" not in sample
+    assert "avg_ops_per_sec" in sample["variants"][DEFAULT_FILTER_POLICY]
+    # D: catalog text not repeated per group
+    fb = sample["variants"][DEFAULT_FILTER_POLICY].get("filter") or {}
+    assert "label" not in fb and "description" not in fb
+    assert fb.get("policy") == DEFAULT_FILTER_POLICY
+    assert "label" in payload["filter_policies"][DEFAULT_FILTER_POLICY]
+    assert not any(str(k).startswith("_") for k in sample)
+    assert not any(str(k).startswith("_") for k in sample["variants"][DEFAULT_FILTER_POLICY])
+
+
 def test_save_baseline_skipped_when_regression(tmp_path):
     """Regression gate must not write a degraded baseline (cli ordering contract)."""
     baseline = tmp_path / "baseline.json"
diff --git a/dashboard/charts.js b/dashboard/charts.js
index 9c7ee951..a9c13dee 100644
--- a/dashboard/charts.js
+++ b/dashboard/charts.js
@@ -1,64 +1,134 @@
-// Chart instances
+import {
+  formatOpsCompact,
+  formatTimeCompact,
+  formatIntGrouped,
+  formatSig,
+  chooseLatencyUnit,
+} from './format.js';
+
 let scatterChartInstance = null;
 let barChartInstance = null;
 
-// Google Material style constants
 const fontStyle = {
   family: "'Roboto', -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif",
-  size: 11
+  size: 11,
 };
 
 const gridColor = 'rgba(0, 0, 0, 0.06)';
 const tickColor = '#5f6368';
 
+/** @type {{ logScale: boolean, rankSort: 'speed' | 'size' }} */
+let chartOptions = { logScale: false, rankSort: 'speed' };
+
 export function initCharts() {
-  console.log("Material visualizations engine initialized.");
+  // charts created on first data
+}
+
+export function setChartLogScale(enabled) {
+  chartOptions.logScale = !!enabled;
+}
+
+export function getChartLogScale() {
+  return chartOptions.logScale;
+}
+
+/** Ranking chart row order: 'speed' (ops/latency) or 'size' (median bytes, compact first). */
+export function setRankSort(sort) {
+  chartOptions.rankSort = sort === 'size' ? 'size' : 'speed';
+}
+
+export function getRankSort() {
+  return chartOptions.rankSort;
 }
 
 export function updateCharts(groups, paretoNames, metric) {
   updateScatterChart(groups, paretoNames, metric);
   updateBarChart(groups, paretoNames, metric);
+  const title = document.getElementById('bar-chart-title');
+  if (title) {
+    title.textContent =
+      metric === 'ops' ? 'Throughput & Size Ranking' : 'Latency & Size Ranking';
+  }
+  const help = document.getElementById('ranking-help');
+  if (help) {
+    const primaryRight = metric === 'ops' ? 'ops/s' : 'latency';
+    const sortLabel =
+      chartOptions.rankSort === 'size'
+        ? 'sorted by size (most compact first)'
+        : metric === 'ops'
+          ? 'sorted by ops/s (highest first)'
+          : 'sorted by latency (lowest first)';
+    help.innerHTML =
+      `Single diverging chart, <strong>${sortLabel}</strong>: ` +
+      `<span class="rank-legend-size">◀ size</span> left · ` +
+      `<span class="rank-legend-speed">${primaryRight} ▶</span> right. ` +
+      `Each side is normalized to the chart max (100); hover for absolute values.`;
+  }
+}
+
+export function exportScatterPng() {
+  if (!scatterChartInstance) return null;
+  return scatterChartInstance.toBase64Image('image/png', 1);
+}
+
+/** Prefer primary ranking chart for PNG export. */
+export function exportBarPng() {
+  if (!barChartInstance) return null;
+  return barChartInstance.toBase64Image('image/png', 1);
 }
 
 function updateScatterChart(groups, paretoNames, metric) {
-  const ctx = document.getElementById('scatter-chart').getContext('2d');
-  if (scatterChartInstance) {
-    scatterChartInstance.destroy();
-  }
+  const canvas = document.getElementById('scatter-chart');
+  if (!canvas) return;
+  const ctx = canvas.getContext('2d');
+  if (scatterChartInstance) scatterChartInstance.destroy();
 
   const isOps = metric === 'ops';
-
   const paretoPoints = [];
   const standardPoints = [];
 
-  groups.forEach(g => {
+  groups.forEach((g) => {
     const xVal = isOps ? g.avg_ops_per_sec : g.avg_time_total_ns;
     const yVal = g.median_size_bytes;
+    if (xVal == null || yVal == null || !Number.isFinite(xVal) || !Number.isFinite(yVal)) return;
+    if (chartOptions.logScale && xVal <= 0) return;
     const point = {
       x: xVal,
       y: yVal,
       label: g.serializer,
       ops: g.avg_ops_per_sec,
-      time: g.avg_time_total_ns
+      time: g.avg_time_total_ns,
+      onFrontier: paretoNames.includes(g.serializer),
     };
-
-    if (paretoNames.includes(g.serializer)) {
-      paretoPoints.push(point);
-    } else {
-      standardPoints.push(point);
-    }
+    if (point.onFrontier) paretoPoints.push(point);
+    else standardPoints.push(point);
   });
 
-  const sortedPareto = [...paretoPoints].sort((a, b) => a.y - b.y);
+  // Axis title unit must match tick scale (raw values stay in ns / ops/s).
+  const latencyNs = isOps
+    ? []
+    : [...standardPoints, ...paretoPoints].map((p) => p.time).filter((v) => Number.isFinite(v));
+  const latencyScale = chooseLatencyUnit(latencyNs);
+  const xAxisTitle = isOps
+    ? 'Throughput (ops/s)'
+    : `Total latency (${latencyScale.unit})`;
+  const formatXTick = (value) => {
+    if (isOps) return formatOpsCompact(value);
+    if (value == null || !Number.isFinite(value)) return '';
+    return formatSig(value / latencyScale.divisor);
+  };
 
+  const sortedPareto = [...paretoPoints].sort((a, b) => a.y - b.y);
   const frontierLineData = [];
   for (let i = 0; i < sortedPareto.length; i++) {
     frontierLineData.push({ x: sortedPareto[i].x, y: sortedPareto[i].y });
     if (i < sortedPareto.length - 1) {
-      frontierLineData.push({ x: sortedPareto[i+1].x, y: sortedPareto[i].y });
+      frontierLineData.push({ x: sortedPareto[i + 1].x, y: sortedPareto[i].y });
     }
   }
 
+  const xType = chartOptions.logScale ? 'logarithmic' : 'linear';
+
   scatterChartInstance = new Chart(ctx, {
     type: 'scatter',
     data: {
@@ -74,30 +144,30 @@ function updateScatterChart(groups, paretoNames, metric) {
           pointRadius: 0,
           fill: false,
           stepped: true,
-          order: 3
+          order: 3,
         },
         {
           label: 'Pareto Optimal',
           data: paretoPoints,
-          backgroundColor: '#1a73e8', // Google Blue
+          backgroundColor: '#1a73e8',
           borderColor: '#ffffff',
           borderWidth: 1.5,
           pointRadius: 7,
           pointHoverRadius: 9,
           pointStyle: 'rectRot',
-          order: 1
+          order: 1,
         },
         {
-          label: 'Sub-Optimal',
+          label: 'Dominated',
           data: standardPoints,
-          backgroundColor: 'rgba(95, 99, 104, 0.4)', // Slate gray
-          borderColor: 'rgba(0, 0, 0, 0.1)',
+          backgroundColor: 'rgba(95, 99, 104, 0.35)',
+          borderColor: 'rgba(0, 0, 0, 0.08)',
           borderWidth: 1,
-          pointRadius: 5,
-          pointHoverRadius: 7,
-          order: 2
-        }
-      ]
+          pointRadius: 4,
+          pointHoverRadius: 6,
+          order: 2,
+        },
+      ],
     },
     options: {
       responsive: true,
@@ -107,10 +177,8 @@ function updateScatterChart(groups, paretoNames, metric) {
           labels: {
             color: tickColor,
             font: fontStyle,
-            filter: function(item) {
-              return item.text !== 'Frontier Line';
-            }
-          }
+            filter: (item) => item.text !== 'Frontier Line',
+          },
         },
         tooltip: {
           backgroundColor: 'rgba(32, 33, 36, 0.95)',
@@ -122,183 +190,261 @@ function updateScatterChart(groups, paretoNames, metric) {
           bodyFont: fontStyle,
           titleFont: { ...fontStyle, weight: 'bold' },
           callbacks: {
-            label: function(context) {
+            label: (context) => {
               const p = context.raw;
-              if (!p.label) return '';
+              if (!p?.label) return '';
               return [
                 `Serializer: ${p.label}`,
-                `Throughput: ${formatOps(p.ops)}`,
-                `Latency: ${formatTime(p.time)}`,
-                `Size: ${p.y} Bytes`
+                `Throughput: ${formatOpsCompact(p.ops)}`,
+                `Latency: ${formatTimeCompact(p.time)}`,
+                `Size: ${formatIntGrouped(p.y)} bytes`,
+                p.onFrontier ? 'On Pareto frontier' : 'Dominated on speed/size',
               ];
-            }
-          }
-        }
+            },
+          },
+        },
       },
       scales: {
         x: {
+          type: xType,
           title: {
             display: true,
-            text: isOps ? 'Throughput (Operations / Second)' : 'Total Latency (Nanoseconds)',
+            text: xAxisTitle,
             color: tickColor,
-            font: { ...fontStyle, weight: 'bold' }
+            font: { ...fontStyle, weight: 'bold' },
           },
           grid: { color: gridColor },
           ticks: {
             color: tickColor,
             font: fontStyle,
-            callback: function(value) {
-              return isOps ? formatOps(value) : formatTime(value);
-            }
-          }
+            callback: (value) => formatXTick(value),
+          },
         },
         y: {
           title: {
             display: true,
-            text: 'Serialized Size (Bytes)',
+            text: 'Serialized size (bytes)',
             color: tickColor,
-            font: { ...fontStyle, weight: 'bold' }
+            font: { ...fontStyle, weight: 'bold' },
           },
           grid: { color: gridColor },
           ticks: {
             color: tickColor,
-            font: fontStyle
-          }
-        }
-      }
+            font: fontStyle,
+            callback: (v) => formatIntGrouped(v),
+          },
+        },
+      },
     },
-    plugins: [{
-      id: 'pointLabels',
-      afterDatasetsDraw(chart) {
-        const {ctx} = chart;
-        ctx.save();
-        ctx.textAlign = 'center';
-        
-        chart.data.datasets.forEach((dataset, datasetIndex) => {
-          // Dataset 0 is the Frontier Line (ignore it)
-          if (datasetIndex === 0) return;
-          
-          const isPareto = datasetIndex === 1;
-          ctx.font = isPareto 
-            ? 'bold 10px "Roboto", -apple-system, sans-serif' 
-            : '400 9px "Roboto", -apple-system, sans-serif';
-          ctx.fillStyle = isPareto ? '#1a73e8' : '#80868b';
-          
-          const meta = chart.getDatasetMeta(datasetIndex);
-          meta.data.forEach((element, index) => {
-            const dataPoint = dataset.data[index];
-            if (dataPoint && dataPoint.label) {
-              const xPos = element.x;
-              const yPos = element.y - (isPareto ? 10 : 8);
-              ctx.fillText(dataPoint.label, xPos, yPos);
-            }
+    plugins: [
+      {
+        id: 'pointLabels',
+        afterDatasetsDraw(chart) {
+          const { ctx: c } = chart;
+          c.save();
+          c.textAlign = 'center';
+          chart.data.datasets.forEach((dataset, datasetIndex) => {
+            if (datasetIndex === 0) return;
+            const isPareto = datasetIndex === 1;
+            if (!isPareto) return;
+            c.font = 'bold 10px "Roboto", -apple-system, sans-serif';
+            c.fillStyle = '#1a73e8';
+            const meta = chart.getDatasetMeta(datasetIndex);
+            meta.data.forEach((element, index) => {
+              const dataPoint = dataset.data[index];
+              if (dataPoint?.label) {
+                c.fillText(dataPoint.label, element.x, element.y - 10);
+              }
+            });
           });
-        });
-        ctx.restore();
-      }
-    }]
+          c.restore();
+        },
+      },
+    ],
   });
 }
 
+/**
+ * Single diverging (butterfly) horizontal bar chart:
+ * - Right (blue): throughput or latency, normalized 0..100 vs chart max
+ * - Left (green): median size, normalized 0..-100 vs chart max
+ * Absolute values only in tooltips — avoids dual-axis collisions.
+ */
 function updateBarChart(groups, paretoNames, metric) {
-  const ctx = document.getElementById('bar-chart').getContext('2d');
-  if (barChartInstance) {
-    barChartInstance.destroy();
-  }
+  const canvas = document.getElementById('bar-chart');
+  if (!canvas) return;
+  if (barChartInstance) barChartInstance.destroy();
 
   const isOps = metric === 'ops';
+  const sortBySize = chartOptions.rankSort === 'size';
 
-  const sortedGroups = [...groups].sort((a, b) => {
-    return isOps 
-      ? b.avg_ops_per_sec - a.avg_ops_per_sec
-      : a.avg_time_total_ns - b.avg_time_total_ns;
-  }).slice(0, 15);
+  const sortedGroups = [...groups]
+    .filter((g) => {
+      if (!g) return false;
+      if (g.median_size_bytes == null && sortBySize) return false;
+      return isOps ? g.avg_ops_per_sec != null : g.avg_time_total_ns != null;
+    })
+    .sort((a, b) => {
+      if (sortBySize) {
+        // Compact first (ascending size); tie-break by speed
+        const ds = (a.median_size_bytes ?? 0) - (b.median_size_bytes ?? 0);
+        if (ds !== 0) return ds;
+      }
+      return isOps
+        ? b.avg_ops_per_sec - a.avg_ops_per_sec
+        : a.avg_time_total_ns - b.avg_time_total_ns;
+    })
+    .slice(0, 15);
 
-  const labels = sortedGroups.map(g => g.serializer);
-  const data = sortedGroups.map(g => isOps ? g.avg_ops_per_sec : g.avg_time_total_ns);
+  const labels = sortedGroups.map((g) => g.serializer);
+  const primaryRaw = sortedGroups.map((g) =>
+    isOps ? g.avg_ops_per_sec : g.avg_time_total_ns
+  );
+  const sizeRaw = sortedGroups.map((g) => Number(g.median_size_bytes) || 0);
+
+  const maxPrimary = Math.max(...primaryRaw.filter((v) => Number.isFinite(v) && v > 0), 1);
+  const maxSize = Math.max(...sizeRaw.filter((v) => Number.isFinite(v) && v > 0), 1);
+
+  // Normalized: speed → +0..100, size → -0..-100 (diverging from center)
+  const speedNorm = primaryRaw.map((v) =>
+    Number.isFinite(v) && maxPrimary > 0 ? (v / maxPrimary) * 100 : 0
+  );
+  const sizeNorm = sizeRaw.map((v) =>
+    Number.isFinite(v) && maxSize > 0 ? -(v / maxSize) * 100 : 0
+  );
 
-  const backgroundColors = sortedGroups.map(g => 
-    paretoNames.includes(g.serializer) 
-      ? 'rgba(26, 115, 232, 0.85)' // Google Blue
-      : '#e8eaed' // High-contrast Material gray
+  const speedColors = sortedGroups.map((g) =>
+    paretoNames.includes(g.serializer) ? 'rgba(26, 115, 232, 0.9)' : 'rgba(26, 115, 232, 0.28)'
   );
-  
-  const borderColors = sortedGroups.map(g => 
-    paretoNames.includes(g.serializer) ? '#1a73e8' : '#bdc1c6'
+  const sizeColors = sortedGroups.map((g) =>
+    paretoNames.includes(g.serializer) ? 'rgba(30, 142, 62, 0.9)' : 'rgba(30, 142, 62, 0.28)'
   );
 
-  barChartInstance = new Chart(ctx, {
+  barChartInstance = new Chart(canvas.getContext('2d'), {
     type: 'bar',
     data: {
-      labels: labels,
-      datasets: [{
-        label: isOps ? 'Ops/Sec' : 'Latency (ns)',
-        data: data,
-        backgroundColor: backgroundColors,
-        borderColor: borderColors,
-        borderWidth: 1,
-        borderRadius: 2
-      }]
+      labels,
+      // Legend order matches plot: size left (←), then speed/latency right (→).
+      datasets: [
+        {
+          label: 'Size (←)',
+          data: sizeNorm,
+          backgroundColor: sizeColors,
+          borderColor: sortedGroups.map((g) =>
+            paretoNames.includes(g.serializer) ? '#1e8e3e' : 'rgba(30, 142, 62, 0.45)'
+          ),
+          borderWidth: 1,
+          borderRadius: 3,
+          barPercentage: 0.9,
+          categoryPercentage: 0.75,
+        },
+        {
+          label: isOps ? 'Ops/s (→)' : 'Latency (→)',
+          data: speedNorm,
+          backgroundColor: speedColors,
+          borderColor: sortedGroups.map((g) =>
+            paretoNames.includes(g.serializer) ? '#1a73e8' : 'rgba(26, 115, 232, 0.45)'
+          ),
+          borderWidth: 1,
+          borderRadius: 3,
+          barPercentage: 0.9,
+          categoryPercentage: 0.75,
+        },
+      ],
     },
     options: {
       indexAxis: 'y',
       responsive: true,
       maintainAspectRatio: false,
       plugins: {
-        legend: { display: false },
+        legend: {
+          display: true,
+          position: 'top',
+          align: 'end',
+          labels: {
+            color: tickColor,
+            font: fontStyle,
+            boxWidth: 12,
+            usePointStyle: true,
+            pointStyle: 'rectRounded',
+          },
+        },
         tooltip: {
           backgroundColor: 'rgba(32, 33, 36, 0.95)',
           titleColor: '#ffffff',
           bodyColor: '#ffffff',
           borderColor: '#dadce0',
           borderWidth: 1,
-          padding: 8,
+          padding: 10,
           bodyFont: fontStyle,
           titleFont: { ...fontStyle, weight: 'bold' },
           callbacks: {
-            label: function(context) {
-              const val = context.raw;
-              return isOps 
-                ? ` Throughput: ${formatOps(val)}`
-                : ` Latency: ${formatTime(val)}`;
-            }
-          }
-        }
+            label: (context) => {
+              const g = sortedGroups[context.dataIndex];
+              if (!g) return '';
+              const pct = Math.abs(context.raw).toFixed(0);
+              // dataset 0 = size (left), 1 = speed/latency (right)
+              if (context.datasetIndex === 0) {
+                return `Size: ${formatIntGrouped(g.median_size_bytes)} bytes  (${pct}% of max in chart)`;
+              }
+              const abs = isOps
+                ? formatOpsCompact(g.avg_ops_per_sec)
+                : formatTimeCompact(g.avg_time_total_ns);
+              return isOps
+                ? `Ops/s: ${abs}  (${pct}% of max in chart)`
+                : `Latency: ${abs}  (${pct}% of max in chart)`;
+            },
+            afterBody: (items) => {
+              const g = sortedGroups[items[0]?.dataIndex];
+              if (!g) return [];
+              return [
+                paretoNames.includes(g.serializer) ? 'Pareto optimal' : 'Dominated on speed/size',
+              ];
+            },
+          },
+        },
       },
       scales: {
         x: {
-          grid: { color: gridColor },
+          stacked: false,
+          min: -100,
+          max: 100,
+          grid: {
+            color: (ctx) =>
+              ctx.tick.value === 0 ? 'rgba(32, 33, 36, 0.35)' : gridColor,
+            lineWidth: (ctx) => (ctx.tick.value === 0 ? 1.5 : 1),
+          },
+          title: {
+            display: true,
+            text: isOps
+              ? '◀ larger size          normalized % of chart max          higher ops/s ▶'
+              : '◀ larger size          normalized % of chart max          higher latency ▶',
+            color: tickColor,
+            font: { ...fontStyle, size: 10 },
+          },
           ticks: {
             color: tickColor,
             font: fontStyle,
-            callback: function(value) {
-              return isOps ? formatOps(value) : formatTime(value);
-            }
-          }
+            stepSize: 25,
+            callback: (value) => {
+              if (value === 0) return '0';
+              const a = Math.abs(value);
+              if (value < 0) return `${a}%`; // size side
+              return `${a}%`;
+            },
+          },
         },
         y: {
+          stacked: false,
           grid: { display: false },
           ticks: {
             color: tickColor,
             font: { ...fontStyle, weight: 'bold' },
-            autoSkip: false
-          }
-        }
-      }
-    }
+            autoSkip: false,
+          },
+        },
+      },
+    },
   });
 }
 
-function formatTime(ns) {
-  if (ns === null || ns === undefined) return '-';
-  if (ns < 1000) return `${ns.toFixed(0)}ns`;
-  if (ns < 1000000) return `${(ns / 1000).toFixed(1)}µs`;
-  return `${(ns / 1000000).toFixed(2)}ms`;
-}
-
-function formatOps(ops) {
-  if (ops === null || ops === undefined) return '-';
-  if (ops < 1000) return `${ops.toFixed(0)}/s`;
-  if (ops < 1000000) return `${(ops / 1000).toFixed(0)}K/s`;
-  return `${(ops / 1000000).toFixed(2)}M/s`;
-}
diff --git a/dashboard/format.js b/dashboard/format.js
new file mode 100644
index 00000000..5993a7ac
--- /dev/null
+++ b/dashboard/format.js
@@ -0,0 +1,283 @@
+/**
+ * Shared number formatting for dashboard tables and charts.
+ *
+ * Contract:
+ * - Continuous metrics: 3 significant digits, unitless cells (unit in header).
+ * - Byte sizes and sample counts: locale-grouped integers (e.g. 29,577).
+ * - Ratio cells: absolute + (ratio×) with better/worse class names.
+ */
+
+const SIG = 3;
+
+/**
+ * Format a finite number to `sig` significant digits in **fixed-point only**
+ * (never scientific / exponential). Examples: 1100 → "1,100", 0.644 → "0.644".
+ */
+export function formatSig(value, sig = SIG) {
+  if (value === null || value === undefined || value === '') return '—';
+  if (typeof value !== 'number' || !Number.isFinite(value)) return String(value);
+  if (value === 0) return '0';
+
+  const abs = Math.abs(value);
+  // Round to `sig` significant digits without using exponential display.
+  const order = Math.floor(Math.log10(abs));
+  const scale = 10 ** (sig - 1 - order);
+  const rounded = Math.round(value * scale) / scale;
+
+  // Fraction digits needed so the least significant digit of `sig` is visible.
+  const decimals = Math.max(0, sig - 1 - order);
+
+  if (decimals === 0) {
+    return Math.round(rounded).toLocaleString('en-US');
+  }
+
+  // Fixed-point with thousands separators; strip trailing zeros after the point.
+  let s = rounded.toLocaleString('en-US', {
+    useGrouping: true,
+    minimumFractionDigits: 0,
+    maximumFractionDigits: decimals,
+  });
+  // Guard: some engines can still emit exp for extreme values — force fixed.
+  if (/e/i.test(s)) {
+    s = rounded.toFixed(decimals).replace(/\.?0+$/, '');
+    // Add grouping to integer part
+    const neg = s.startsWith('-');
+    const body = neg ? s.slice(1) : s;
+    const [ip, fp] = body.split('.');
+    const grouped = Number(ip).toLocaleString('en-US');
+    s = (neg ? '-' : '') + grouped + (fp != null && fp !== '' ? `.${fp}` : '');
+  }
+  return s;
+}
+
+/**
+ * Docs Summary-table style label: ``simd-json:0.14.3`` when version is known.
+ * Matches analysis/reports.py: ``f"{name}:{version}" if version else name``.
+ */
+export function serializerDisplayName(serializer, version) {
+  const name = serializer == null ? '' : String(serializer).trim();
+  if (!name) return '—';
+  const ver =
+    version == null || version === ''
+      ? ''
+      : String(version).trim();
+  if (!ver || ver === 'unknown' || ver === '—') return name;
+  // Avoid double-suffix if caller already passed "name:ver"
+  if (name.includes(':') && name.endsWith(ver)) return name;
+  return `${name}:${ver}`;
+}
+
+/** Label from a stats group object (uses serializer_version when present). */
+export function serializerLabelFromGroup(g) {
+  if (!g) return '—';
+  return serializerDisplayName(g.serializer, g.serializer_version);
+}
+
+/** Locale-grouped integer (sizes, counts). */
+export function formatIntGrouped(value) {
+  if (value === null || value === undefined || value === '') return '—';
+  if (typeof value !== 'number' || !Number.isFinite(value)) return String(value);
+  return Math.round(value).toLocaleString('en-US');
+}
+
+/** Fixed µs scale for roster/compare latency columns. */
+export const LATENCY_US = { unit: 'µs', divisor: 1e3, header: 'µs' };
+
+/**
+ * Choose latency display unit from a set of ns values.
+ *
+ * Prefer **microseconds** for table columns. Serializer encode/decode times
+ * usually sit in the µs–ms band: ms collapses fast codecs to awkward decimals
+ * (e.g. 0.012 ms vs 12.3 µs), while a fixed µs scale keeps 3-sig values
+ * comparable across total / ser / deser without unit hopping when one slow
+ * row would otherwise force the whole column into milliseconds.
+ *
+ * - max < 1 µs  → ns (sub-microsecond niche)
+ * - otherwise   → µs (including multi-ms latencies, shown as e.g. 12,400)
+ * - never auto-ms for roster/compare tables
+ */
+export function chooseLatencyUnit(valuesNs) {
+  const nums = (valuesNs || []).filter((v) => typeof v === 'number' && Number.isFinite(v) && v > 0);
+  if (!nums.length) return LATENCY_US;
+  const max = Math.max(...nums);
+  if (max < 1e3) return { unit: 'ns', divisor: 1, header: 'ns' };
+  return LATENCY_US;
+}
+
+/** Choose throughput scale from ops/s values. */
+export function chooseOpsUnit(valuesOps) {
+  const nums = (valuesOps || []).filter((v) => typeof v === 'number' && Number.isFinite(v) && v > 0);
+  if (!nums.length) return { unit: 'ops', divisor: 1, header: 'Ops/s' };
+  const max = Math.max(...nums);
+  if (max >= 1e6) return { unit: 'M', divisor: 1e6, header: 'Ops/s (M)' };
+  if (max >= 1e3) return { unit: 'k', divisor: 1e3, header: 'Ops/s (k)' };
+  return { unit: 'ops', divisor: 1, header: 'Ops/s' };
+}
+
+export function formatLatencyCell(ns, scale) {
+  if (ns === null || ns === undefined || !Number.isFinite(ns)) return '—';
+  const s = scale || { divisor: 1 };
+  return formatSig(ns / s.divisor);
+}
+
+export function formatOpsCell(ops, scale) {
+  if (ops === null || ops === undefined || !Number.isFinite(ops)) return '—';
+  const s = scale || { divisor: 1 };
+  return formatSig(ops / s.divisor);
+}
+
+/**
+ * Compact formats WITH unit — for chart tooltips/axes only (not table cells).
+ */
+export function formatTimeCompact(ns) {
+  if (ns === null || ns === undefined || !Number.isFinite(ns)) return '—';
+  if (ns < 1000) return `${formatSig(ns)} ns`;
+  if (ns < 1e6) return `${formatSig(ns / 1e3)} µs`;
+  return `${formatSig(ns / 1e6)} ms`;
+}
+
+export function formatOpsCompact(ops) {
+  if (ops === null || ops === undefined || !Number.isFinite(ops)) return '—';
+  if (ops < 1000) return `${formatSig(ops)}/s`;
+  if (ops < 1e6) return `${formatSig(ops / 1e3)}k/s`;
+  return `${formatSig(ops / 1e6)}M/s`;
+}
+
+/** Infer metric kind for table formatting. */
+export function metricKind(key) {
+  if (!key) return 'other';
+  if (key.endsWith('_ns') || key.includes('_time_') || key.includes('latency')) return 'latency';
+  if (
+    key.includes('ops_per_sec') ||
+    key.endsWith('_ops_mean') ||
+    key.endsWith('_ops_median') ||
+    key.endsWith('_ops_p95')
+  ) {
+    return 'ops';
+  }
+  if (key.endsWith('_bytes') || key.startsWith('size_') || key === 'median_size_bytes') return 'bytes';
+  if (
+    key === 'runs' ||
+    key === 'runs_raw' ||
+    key === 'outliers_removed' ||
+    key === 'values_clipped' ||
+    key === 'warmup_skipped'
+  )
+    return 'count';
+  if (typeof key === 'string' && (key.includes('fidelity') || key.includes('cv') || key.includes('delta') || key.includes('hedges'))) {
+    return 'ratio';
+  }
+  return 'other';
+}
+
+/**
+ * Format a metric cell value without unit suffix.
+ * Optional `scales` map: { latency: chooseLatencyUnit(...), ops: chooseOpsUnit(...) }
+ */
+export function formatMetricCell(key, value, scales = {}) {
+  if (value === null || value === undefined || value === '') return '—';
+  if (typeof value === 'boolean') return value ? 'true' : 'false';
+  if (typeof value === 'string') return value;
+  if (typeof value !== 'number' || !Number.isFinite(value)) return String(value);
+
+  const kind = metricKind(key);
+  if (kind === 'latency') return formatLatencyCell(value, scales.latency);
+  if (kind === 'ops') return formatOpsCell(value, scales.ops);
+  if (kind === 'bytes' || kind === 'count') return formatIntGrouped(value);
+  if (kind === 'ratio') return formatSig(value);
+  if (Number.isInteger(value) && Math.abs(value) < 1e9) return formatIntGrouped(value);
+  return formatSig(value);
+}
+
+/** Header label with unit for a metric key given column scales. */
+export function metricHeaderLabel(key, scales = {}) {
+  const kind = metricKind(key);
+  const base = key
+    .replace(/_ns$/g, '')
+    .replace(/_bytes$/g, '')
+    .replace(/_per_sec$/g, '')
+    .replace(/_/g, ' ');
+
+  if (kind === 'latency') {
+    const u = scales.latency?.header || 'ns';
+    return `${base} (${u})`;
+  }
+  if (kind === 'ops') {
+    return scales.ops?.header || 'Ops/s';
+  }
+  if (kind === 'bytes') {
+    return key.includes('memory') ? `${base} (bytes)` : `${base} (bytes)`;
+  }
+  return base;
+}
+
+/**
+ * Ratio = value / reference.
+ * @param {string} [ratioTag=''] suffix after ×, e.g. '' → "0.93×", 'med' → "0.93×med", 'base' → "0.93×base"
+ * Returns { text, ratio, className } for cell rendering.
+ */
+export function formatRelativeCell(value, reference, higherIsBetter, scales, key, ratioTag = '') {
+  const abs =
+    key && (String(key).startsWith('ops_') || key === 'avg_ops_per_sec')
+      ? formatOpsCell(value, scales?.ops)
+      : formatMetricCell(key, value, scales);
+  if (
+    value === null ||
+    value === undefined ||
+    reference === null ||
+    reference === undefined ||
+    typeof value !== 'number' ||
+    typeof reference !== 'number' ||
+    !Number.isFinite(value) ||
+    !Number.isFinite(reference) ||
+    reference === 0
+  ) {
+    return { text: abs, ratio: null, className: 'num' };
+  }
+
+  const ratio = value / reference;
+  // Multiplier: 2 significant digits is enough (0.931× → 0.93×)
+  const tag = ratioTag ? `×${ratioTag}` : '×';
+  const ratioText = `${formatSig(ratio, 2)}${tag}`;
+  let className = 'num rel-neutral';
+  if (higherIsBetter === true || higherIsBetter === false) {
+    const better = higherIsBetter ? ratio > 1 + 1e-9 : ratio < 1 - 1e-9;
+    const worse = higherIsBetter ? ratio < 1 - 1e-9 : ratio > 1 + 1e-9;
+    if (better) className = 'num rel-better';
+    else if (worse) className = 'num rel-worse';
+  }
+  return {
+    text: `${abs} (${ratioText})`,
+    ratio,
+    className,
+  };
+}
+
+/** Build latency/ops scales from a list of groups for consistent columns. */
+export function scalesFromGroups(groups, keys = null) {
+  const gs = groups || [];
+  const lat = [];
+  const ops = [];
+  for (const g of gs) {
+    if (!g) continue;
+    if (!keys) {
+      if (typeof g.avg_time_total_ns === 'number') lat.push(g.avg_time_total_ns);
+      if (typeof g.avg_time_ser_ns === 'number') lat.push(g.avg_time_ser_ns);
+      if (typeof g.avg_time_deser_ns === 'number') lat.push(g.avg_time_deser_ns);
+      if (typeof g.avg_ops_per_sec === 'number') ops.push(g.avg_ops_per_sec);
+    } else {
+      for (const k of keys) {
+        const v = g[k];
+        if (typeof v !== 'number' || !Number.isFinite(v)) continue;
+        const kind = metricKind(k);
+        if (kind === 'latency') lat.push(v);
+        if (kind === 'ops') ops.push(v);
+      }
+    }
+  }
+  return {
+    // Tables always normalize latency to µs (see chooseLatencyUnit).
+    latency: lat.length ? chooseLatencyUnit(lat) : LATENCY_US,
+    ops: chooseOpsUnit(ops),
+  };
+}
diff --git a/dashboard/index.css b/dashboard/index.css
index f46d0d51..366cb4d7 100644
--- a/dashboard/index.css
+++ b/dashboard/index.css
@@ -40,42 +40,86 @@ body {
   overflow-x: hidden;
 }
 
-/* Header & Google Style Navbar */
+/* Header & responsive navbar */
 header {
   background: var(--bg-surface);
-  padding: 0.75rem 1.5rem;
-  display: flex;
-  justify-content: space-between;
-  align-items: center;
+  padding: 0.45rem 1.25rem;
   border-bottom: 1px solid var(--border-color);
   position: sticky;
   top: 0;
   z-index: 100;
+  display: flex;
+  flex-wrap: wrap;
+  align-items: center;
+  justify-content: space-between;
+  gap: 0.35rem;
+}
+
+.header-bar {
+  display: flex;
+  align-items: center;
+  justify-content: space-between;
+  gap: 0.75rem;
+  flex: 1 1 auto;
+  min-width: 0;
 }
 
 .logo {
   display: flex;
   align-items: center;
   gap: 0.5rem;
+  min-width: 0;
 }
 
 .logo-icon {
-  font-size: 1.25rem;
   color: var(--color-blue);
-  font-weight: bold;
+  display: flex;
+  align-items: center;
+  flex-shrink: 0;
 }
 
 .logo h1 {
-  font-size: 1.15rem;
+  font-size: 1.05rem;
   font-weight: 500;
   color: var(--text-primary);
   letter-spacing: -0.2px;
+  white-space: nowrap;
+  overflow: hidden;
+  text-overflow: ellipsis;
+}
+
+.nav-toggle {
+  display: none;
+  flex-direction: column;
+  justify-content: center;
+  gap: 4px;
+  width: 40px;
+  height: 40px;
+  padding: 8px;
+  border: 1px solid var(--border-color);
+  border-radius: 6px;
+  background: var(--bg-surface);
+  cursor: pointer;
+}
+
+.nav-toggle-bar {
+  display: block;
+  height: 2px;
+  width: 100%;
+  background: var(--text-primary);
+  border-radius: 1px;
+}
+
+.main-nav {
+  flex: 0 1 auto;
 }
 
 .nav-links {
   display: flex;
-  gap: 0.5rem;
+  flex-wrap: wrap;
+  gap: 0.35rem;
   list-style: none;
+  align-items: center;
 }
 
 .nav-links a {
@@ -83,9 +127,10 @@ header {
   text-decoration: none;
   font-size: 0.85rem;
   font-weight: 500;
-  padding: 0.4rem 0.8rem;
+  padding: 0.45rem 0.75rem;
   border-radius: 4px;
   transition: all 0.15s ease;
+  display: inline-block;
 }
 
 .nav-links a:hover {
@@ -99,14 +144,45 @@ header {
   font-weight: 500;
 }
 
+.nav-docs {
+  border: 1px solid var(--border-color);
+  font-weight: 500;
+}
+
+@media (max-width: 720px) {
+  header {
+    padding: 0.6rem 0.85rem;
+  }
+  .nav-toggle {
+    display: flex;
+  }
+  .main-nav {
+    display: none;
+    width: 100%;
+    flex-basis: 100%;
+  }
+  .main-nav.open {
+    display: block;
+  }
+  .nav-links {
+    flex-direction: column;
+    align-items: stretch;
+    gap: 0.25rem;
+    padding-top: 0.35rem;
+  }
+  .nav-links a {
+    padding: 0.65rem 0.75rem;
+  }
+}
+
 /* Main Container Layout (High Density) */
 .container {
   max-width: 1440px;
   margin: 0 auto;
-  padding: 1rem 1.5rem 2rem 1.5rem;
+  padding: 0.65rem 1.25rem 1.75rem 1.25rem;
   display: flex;
   flex-direction: column;
-  gap: 1rem;
+  gap: 0.55rem;
 }
 
 /* Material Flat Card */
@@ -125,22 +201,55 @@ header {
 }
 
 /* Filters Toolbar */
+.filter-policy-meta {
+  margin: 0;
+  padding: 0.35rem 0.7rem;
+  font-size: 0.8rem;
+  color: var(--text-secondary);
+  line-height: 1.3;
+}
+
+.filter-policy-meta-text strong {
+  color: var(--text-primary);
+  font-weight: 500;
+}
+
+.filter-policy-meta-text .fp-criteria {
+  color: var(--text-muted);
+}
+
 .toolbar {
   display: flex;
   flex-wrap: wrap;
-  gap: 1rem;
+  gap: 0.55rem 0.85rem;
   align-items: center;
   justify-content: space-between;
-  padding: 0.75rem 1rem;
+  padding: 0.45rem 0.75rem;
 }
 
+
 .filter-group {
   display: flex;
   flex-wrap: wrap;
-  gap: 0.75rem;
+  gap: 0.45rem 0.6rem;
   align-items: center;
 }
 
+/* `.display: flex` beats the UA [hidden] rule — keep hide reliable */
+.filter-group[hidden],
+.xl-add-panel[hidden],
+.compare-inline-add[hidden],
+.chip-groups[hidden],
+#compare-same-panel[hidden],
+#compare-xl-filters[hidden],
+#compare-same-filters[hidden],
+#compare-xl-disclaimer[hidden],
+#same-selection-chips[hidden],
+#xl-selection-chips[hidden],
+[hidden] {
+  display: none !important;
+}
+
 .filter-label {
   font-size: 0.75rem;
   font-weight: 700;
@@ -158,7 +267,7 @@ select {
   background: var(--bg-surface);
   border: 1px solid var(--border-color);
   border-radius: 4px;
-  padding: 0.4rem 2rem 0.4rem 0.75rem;
+  padding: 0.3rem 1.75rem 0.3rem 0.6rem;
   color: var(--text-primary);
   font-family: var(--font-family);
   font-size: 0.85rem;
@@ -195,7 +304,7 @@ select:focus {
   border: none;
   border-right: 1px solid var(--border-color);
   color: var(--text-secondary);
-  padding: 0.4rem 0.8rem;
+  padding: 0.3rem 0.7rem;
   font-family: var(--font-family);
   font-size: 0.85rem;
   font-weight: 500;
@@ -220,16 +329,16 @@ select:focus {
 /* KPI Cards Layout (Horizontal Row & Small) */
 .summary-grid {
   display: grid;
-  grid-template-columns: repeat(auto-fit, minmax(220px, 1fr));
-  gap: 1rem;
+  grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
+  gap: 0.55rem;
 }
 
 .kpi-card {
   display: flex;
   flex-direction: column;
-  gap: 0.25rem;
+  gap: 0.1rem;
   position: relative;
-  padding: 0.75rem 1rem;
+  padding: 0.5rem 0.75rem;
 }
 
 .kpi-card::before {
@@ -242,8 +351,18 @@ select:focus {
   background: var(--color-blue);
 }
 
-.kpi-card.purple::before {
-  background: #a142f4;
+.kpi-card.featured::before {
+  background: #a142f4; /* featured highlight only — never negative status */
+}
+
+.kpi-card {
+  min-height: 0;
+}
+
+.kpi-value-name {
+  font-size: 1.15rem !important;
+  line-height: 1.25 !important;
+  word-break: break-word;
 }
 
 .kpi-card.green::before {
@@ -251,7 +370,7 @@ select:focus {
 }
 
 .kpi-title {
-  font-size: 0.75rem;
+  font-size: 0.7rem;
   font-weight: 500;
   text-transform: uppercase;
   letter-spacing: 0.5px;
@@ -259,14 +378,16 @@ select:focus {
 }
 
 .kpi-value {
-  font-size: 1.4rem;
+  font-size: 1.25rem;
   font-weight: 500;
   color: var(--text-primary);
+  line-height: 1.2;
 }
 
 .kpi-desc {
-  font-size: 0.75rem;
+  font-size: 0.7rem;
   color: var(--text-muted);
+  line-height: 1.25;
 }
 
 /* High Density Charts Container */
@@ -415,56 +536,63 @@ select:focus {
   gap: 0.6rem;
 }
 
-.cross-lang-add-row {
-  display: flex;
-  flex-wrap: wrap;
-  align-items: center;
-  justify-content: flex-start;
-  gap: 0.6rem;
-}
+/* (cross-lang add controls live in .compare-inline-add / #xl-add-panel) */
 
-/* Keep language + serializer + Add as a tight group (do not stretch the
-   serializer wrapper — a flex:1 wrapper left the custom ::after chevron
-   stranded at the far right of the row). */
-.cross-lang-add-row .select-wrapper {
-  flex: 0 0 auto;
+/* Compare selection chips (neutral; baseline emphasized) */
+.chip-groups,
+.xl-chips {
+  display: flex;
+  flex-direction: column;
+  gap: 0.45rem;
+  min-height: 1.5rem;
+  margin-top: 0.35rem;
 }
 
-.cross-lang-add-row .xl-add-ser-wrap select {
-  min-width: 12rem;
-  max-width: 22rem;
+.chip-lang-row {
+  display: flex;
+  flex-wrap: wrap;
+  align-items: center;
+  gap: 0.35rem 0.5rem;
 }
 
-.cross-lang-add-row .xl-add-btn {
-  flex: 0 0 auto;
-  font-size: 0.85rem;
-  border: 1px solid var(--border-color);
+.chip-lang-label {
+  flex: 0 0 4.5rem;
+  font-size: 0.68rem;
+  font-weight: 600;
+  text-transform: uppercase;
+  letter-spacing: 0.04em;
+  color: var(--text-muted);
 }
 
-.xl-chips {
+.chip-lang-chips {
   display: flex;
   flex-wrap: wrap;
-  gap: 0.4rem;
-  min-height: 2rem;
+  gap: 0.35rem;
+  flex: 1 1 auto;
+  min-width: 0;
 }
 
 .xl-chip {
   display: inline-flex;
   align-items: center;
-  gap: 0.35rem;
-  background: var(--bg-blue-light);
-  color: var(--color-blue);
-  border: 1px solid #c6dafc;
+  gap: 0.3rem;
+  background: var(--bg-surface);
+  color: var(--text-primary);
+  border: 1px solid var(--border-color);
   border-radius: 999px;
-  padding: 0.2rem 0.35rem 0.2rem 0.65rem;
+  padding: 0.2rem 0.3rem 0.2rem 0.6rem;
   font-size: 0.78rem;
   font-weight: 500;
   max-width: 100%;
 }
 
+.xl-chip.chip-baseline {
+  border-color: var(--color-blue);
+  background: var(--bg-blue-light);
+  color: var(--color-blue);
+}
+
 .xl-chip.pareto-chip {
-  background: var(--bg-green-light);
-  color: var(--color-green);
   border-color: #b7e1c4;
 }
 
@@ -472,7 +600,17 @@ select:focus {
   overflow: hidden;
   text-overflow: ellipsis;
   white-space: nowrap;
-  max-width: 16rem;
+  max-width: 14rem;
+}
+
+.xl-chip-ver {
+  font-weight: 400;
+  color: var(--text-muted);
+  font-size: 0.72rem;
+}
+
+.xl-chip.chip-baseline .xl-chip-ver {
+  color: #5a8fd4;
 }
 
 .xl-chip-remove {
@@ -484,7 +622,7 @@ select:focus {
   line-height: 1;
   padding: 0.1rem 0.35rem;
   border-radius: 999px;
-  opacity: 0.75;
+  opacity: 0.65;
 }
 
 .xl-chip-remove:hover {
@@ -492,6 +630,11 @@ select:focus {
   background: rgba(0, 0, 0, 0.06);
 }
 
+.chip-empty {
+  color: var(--text-muted);
+  font-size: 0.85rem;
+}
+
 .xl-table-wrap {
   border: 1px solid var(--border-color);
   border-radius: 6px;
@@ -775,6 +918,33 @@ select:focus {
   }
 }
 
+/* Detailed Analytics: Ops vs Latency column sets (local switch) */
+#analytics-table.view-ops .roster-col-latency {
+  display: none;
+}
+#analytics-table.view-latency .roster-col-ops {
+  display: none;
+}
+
+/* Pareto highlight instead of Frontier column */
+#analytics-table tbody tr.roster-pareto-row td {
+  background: rgba(26, 115, 232, 0.06);
+}
+#analytics-table tbody tr.roster-pareto-row td.str strong {
+  color: var(--color-blue);
+}
+#analytics-table tbody tr.roster-pareto-row.roster-baseline-row td {
+  background: var(--bg-blue-light);
+}
+
+.roster-metric-tabs {
+  flex-shrink: 0;
+}
+.roster-metric-tabs .tab-btn {
+  font-size: 0.8rem;
+  padding: 0.3rem 0.65rem;
+}
+
 /* Detailed Data Table (Material Design) */
 .table-panel {
   padding-bottom: 0.5rem;
@@ -945,3 +1115,813 @@ footer {
 ::-webkit-scrollbar-thumb:hover {
   background: #bdc1c6;
 }
+
+
+/* --- Dashboard improvement tokens --- */
+.badge-slate {
+  background: #e8eaed;
+  color: #5f6368;
+}
+
+.section-help {
+  font-size: 0.85rem;
+  color: var(--text-secondary);
+  margin: 0.25rem 0 0.75rem 0;
+  line-height: 1.45;
+  font-weight: 400;
+}
+
+.section-disclaimer {
+  font-size: 0.85rem;
+  color: #5f4b00;
+  background: var(--bg-yellow-light);
+  border: 1px solid #f9ab00;
+  border-radius: 6px;
+  padding: 0.6rem 0.85rem;
+  margin: 0 0 0.75rem 0;
+}
+
+.run-meta {
+  padding: 0.3rem 0.7rem;
+  font-size: 0.75rem;
+  color: var(--text-secondary);
+  line-height: 1.3;
+}
+
+.run-meta-text {
+  font-variant-numeric: tabular-nums;
+}
+
+.chart-toolbar {
+  display: flex;
+  align-items: center;
+  gap: 0.4rem;
+  flex-wrap: wrap;
+}
+
+.chart-tool-btn {
+  font-size: 0.75rem !important;
+  padding: 0.25rem 0.5rem !important;
+}
+
+.chart-container-tall {
+  height: 360px;
+}
+
+.ranking-help {
+  margin: 0 0 0.5rem 0;
+  font-size: 0.8rem;
+}
+
+.rank-legend-size {
+  color: #1e8e3e;
+  font-weight: 600;
+}
+
+.rank-legend-speed {
+  color: #1a73e8;
+  font-weight: 600;
+}
+
+.ranking-chart-single {
+  height: 420px;
+}
+
+.table-header-actions {
+  display: flex;
+  align-items: center;
+  gap: 0.5rem;
+  flex-wrap: wrap;
+}
+
+.data-table th.num,
+.data-table td.num {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+  font-family: ui-monospace, SFMono-Regular, "SF Mono", Menlo, Consolas, monospace;
+  font-size: 0.82rem;
+}
+
+.data-table th.str,
+.data-table td.str {
+  text-align: left;
+}
+
+.data-table th.status,
+.data-table td.status {
+  text-align: center;
+}
+
+.data-table tbody tr:nth-child(even) td {
+  background: rgba(0, 0, 0, 0.015);
+}
+
+.data-table tbody tr:hover td {
+  background: #f1f3f4;
+}
+
+td.rel-better {
+  color: var(--color-green);
+  background: var(--bg-green-light) !important;
+}
+
+td.rel-worse {
+  color: var(--color-red);
+  background: var(--bg-red-light) !important;
+}
+
+td.rel-neutral {
+  color: var(--text-secondary);
+}
+
+th.baseline-col {
+  background: var(--bg-blue-light) !important;
+  color: var(--color-blue);
+}
+
+tr.roster-baseline-row td {
+  background: var(--bg-blue-light) !important;
+}
+
+tr.roster-baseline-row td.num.baseline-col {
+  font-weight: 600;
+}
+
+.compare-lab-filters {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 0.75rem;
+  margin-bottom: 0.75rem;
+  align-items: center;
+}
+
+.compare-scope-tabs {
+  margin-bottom: 0.75rem;
+}
+
+/* Must stay row — column was stacking lang/ser/Add and blowing vertical space */
+.xl-add-panel {
+  margin-top: 0;
+  display: flex;
+  flex-direction: row;
+  flex-wrap: nowrap;
+  align-items: center;
+  gap: 0.3rem;
+}
+
+.xl-add-panel[hidden] {
+  display: none !important;
+}
+
+.utility-card {
+  gap: 0.75rem;
+}
+
+.utility-card-title {
+  font-size: 0.95rem;
+  font-weight: 500;
+  color: var(--text-primary);
+}
+
+.utility-actions {
+  display: grid;
+  grid-template-columns: repeat(2, 1fr);
+  gap: 0.5rem;
+  margin-top: 0.5rem;
+}
+
+.dropzone {
+  border: 2px dashed var(--border-color);
+}
+
+.dropzone.dragover {
+  border-color: var(--color-blue);
+  background: var(--bg-blue-light);
+}
+
+#serializer-metrics-table td.num {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+  font-family: ui-monospace, SFMono-Regular, "SF Mono", Menlo, Consolas, monospace;
+  font-size: 0.82rem;
+}
+
+
+/* --- Compare lab: compact controls + matrix headers --- */
+.compare-title-row {
+  margin-bottom: 0.5rem;
+}
+
+.compare-title-left {
+  display: flex;
+  flex-wrap: wrap;
+  align-items: center;
+  gap: 0.5rem 0.75rem;
+  min-width: 0;
+}
+
+.compare-status-line {
+  font-size: 0.8rem;
+  color: var(--text-secondary);
+  font-variant-numeric: tabular-nums;
+}
+
+.compare-controls-compact {
+  display: flex;
+  flex-direction: column;
+  gap: 0.3rem;
+  margin-bottom: 0.5rem;
+  padding: 0.4rem 0.55rem;
+  background: #f8f9fa;
+  border: 1px solid var(--border-color);
+  border-radius: 8px;
+}
+
+.compare-ctrl-row {
+  display: flex;
+  flex-wrap: wrap;
+  align-items: center;
+  gap: 0.3rem 0.5rem;
+}
+
+.compare-ctrl-row-selected,
+.compare-ctrl-row-metrics {
+  padding-top: 0.3rem;
+  border-top: 1px solid var(--border-color);
+}
+
+.compare-lab-filters-inline {
+  gap: 0.3rem;
+}
+
+.compare-lab-filters-inline .select-wrapper select {
+  max-width: 14rem;
+  font-size: 0.8rem;
+  padding: 0.28rem 1.6rem 0.28rem 0.5rem;
+}
+
+.compare-inline-add {
+  display: flex;
+  flex-wrap: nowrap;
+  align-items: center;
+  gap: 0.3rem;
+  flex: 1 1 auto;
+  min-width: 0;
+}
+
+#xl-add-panel.compare-inline-add,
+#xl-add-panel.xl-add-panel {
+  flex: 0 0 auto;
+  flex-direction: row !important;
+  flex-wrap: nowrap !important;
+  justify-content: flex-start;
+  align-items: center;
+  margin-top: 0;
+  gap: 0.3rem;
+  width: auto;
+  max-width: none;
+}
+
+#xl-add-panel .select-wrapper {
+  flex: 0 0 auto;
+  display: inline-block;
+  position: relative;
+  width: auto;
+}
+
+#xl-add-panel #xl-add-lang {
+  width: 5.25rem;
+  max-width: 5.25rem;
+  min-width: 5.25rem;
+  font-size: 0.78rem;
+  padding: 0.25rem 1.35rem 0.25rem 0.4rem;
+}
+
+#xl-add-panel .xl-add-ser-wrap {
+  flex: 0 0 auto;
+  width: 11rem;
+  max-width: 11rem;
+  min-width: 11rem;
+}
+
+#xl-add-panel .xl-add-ser-wrap select {
+  width: 100%;
+  font-size: 0.78rem;
+  padding: 0.25rem 1.35rem 0.25rem 0.4rem;
+}
+
+#xl-add-panel #xl-add-btn {
+  flex: 0 0 auto;
+}
+
+.compare-sel-actions {
+  margin-left: 0;
+  flex-shrink: 0;
+  display: flex;
+  gap: 0.35rem;
+  align-items: center;
+}
+
+.compare-search-input {
+  flex: 0 1 7rem;
+  min-width: 5rem;
+  max-width: 9rem;
+  background: var(--bg-surface);
+  border: 1px solid var(--border-color);
+  border-radius: 4px;
+  padding: 0.28rem 0.45rem;
+  font-family: var(--font-family);
+  font-size: 0.78rem;
+  color: var(--text-primary);
+  outline: none;
+}
+
+.compare-search-input:focus {
+  border-color: var(--color-blue);
+}
+
+.compare-add-select-wrap {
+  flex: 1 1 9rem;
+  min-width: 7rem;
+  max-width: 14rem;
+}
+
+.compare-add-select-wrap select {
+  width: 100%;
+  padding-top: 0.28rem;
+  padding-bottom: 0.28rem;
+  font-size: 0.78rem;
+}
+
+/* Chips: one dense wrapping stream (lang rows stay inline, not stacked blocks) */
+.chip-groups-compact {
+  display: flex;
+  flex-direction: row;
+  flex-wrap: wrap;
+  align-items: center;
+  gap: 0.2rem 0.45rem;
+  margin-top: 0;
+  max-height: 3.4rem;
+  overflow-x: hidden;
+  overflow-y: auto;
+  padding: 0.1rem 0;
+}
+
+.chip-groups-compact .chip-lang-row {
+  display: inline-flex;
+  flex-wrap: wrap;
+  align-items: center;
+  gap: 0.2rem 0.25rem;
+  margin: 0;
+}
+
+.chip-groups-compact .chip-lang-label {
+  flex: 0 0 auto;
+  flex-basis: auto;
+  width: auto;
+  min-width: 0;
+  font-size: 0.62rem;
+  margin: 0;
+  padding: 0;
+}
+
+.chip-groups-compact .chip-lang-chips {
+  display: inline-flex;
+  flex-wrap: wrap;
+  gap: 0.2rem;
+}
+
+.chip-groups-compact .xl-chip {
+  font-size: 0.7rem;
+  padding: 0.08rem 0.2rem 0.08rem 0.4rem;
+  max-width: 11rem;
+}
+
+.chip-groups-compact .xl-chip-label {
+  max-width: 8.5rem;
+}
+
+.chip-groups-compact .chip-empty {
+  font-size: 0.75rem;
+  padding: 0;
+}
+
+.comparison-section .preset-btn {
+  font-size: 0.7rem;
+  padding: 0.18rem 0.4rem;
+}
+
+.comparison-section .metrics-panel-body {
+  max-height: 160px;
+  margin-top: 0.25rem;
+  padding-top: 0.25rem;
+}
+
+.comparison-section .section-disclaimer {
+  font-size: 0.78rem;
+  padding: 0.4rem 0.6rem;
+  margin: 0 0 0.4rem 0;
+}
+
+.comparison-section .compare-scope-tabs .tab-btn {
+  font-size: 0.78rem;
+  padding: 0.28rem 0.55rem;
+}
+
+.comparison-section .filter-label {
+  font-size: 0.68rem;
+}
+
+/* Compare matrix: non-overlapping stacked headers */
+.compare-table-wrap {
+  margin-top: 0;
+}
+
+#serializer-metrics-table.compare-matrix-table {
+  table-layout: auto;
+  border-collapse: separate;
+  border-spacing: 0;
+  width: max-content;
+  min-width: 100%;
+}
+
+#serializer-metrics-table.compare-matrix-table th.cmp-th-metric {
+  position: sticky;
+  left: 0;
+  z-index: 3;
+  min-width: 9rem;
+  max-width: 14rem;
+  text-align: left;
+  vertical-align: bottom;
+  background: #f1f3f4;
+}
+
+#serializer-metrics-table.compare-matrix-table th.cmp-th-ser {
+  min-width: 8.5rem;
+  width: 8.5rem;
+  max-width: none;
+  padding: 0.45rem 0.5rem;
+  text-align: center;
+  vertical-align: bottom;
+  white-space: normal;
+  overflow: hidden;
+  line-height: 1.15;
+  font-weight: 500;
+  border-left: 1px solid var(--border-color);
+  background: #f1f3f4;
+}
+
+#serializer-metrics-table.compare-matrix-table th.cmp-th-ser.baseline-col {
+  background: var(--bg-blue-light) !important;
+  color: var(--color-blue);
+}
+
+#serializer-metrics-table.compare-matrix-table .cmp-th-lang {
+  display: block;
+  font-size: 0.62rem;
+  font-weight: 600;
+  text-transform: uppercase;
+  letter-spacing: 0.03em;
+  color: var(--text-muted);
+  margin-bottom: 0.1rem;
+}
+
+#serializer-metrics-table.compare-matrix-table .cmp-th-name {
+  display: block;
+  font-size: 0.72rem;
+  font-weight: 600;
+  color: inherit;
+  overflow: hidden;
+  text-overflow: ellipsis;
+  white-space: nowrap;
+  max-width: 100%;
+}
+
+#serializer-metrics-table.compare-matrix-table .cmp-th-ver {
+  display: block;
+  font-size: 0.65rem;
+  font-weight: 400;
+  color: var(--text-muted);
+  overflow: hidden;
+  text-overflow: ellipsis;
+  white-space: nowrap;
+}
+
+#serializer-metrics-table.compare-matrix-table .cmp-th-base {
+  display: block;
+  font-size: 0.6rem;
+  font-weight: 600;
+  text-transform: uppercase;
+  letter-spacing: 0.04em;
+  color: var(--color-blue);
+  margin-top: 0.15rem;
+}
+
+#serializer-metrics-table.compare-matrix-table td.num {
+  min-width: 8.5rem;
+  width: 8.5rem;
+  max-width: none;
+  padding: 0.45rem 0.5rem;
+  text-align: right;
+  border-left: 1px solid rgba(0, 0, 0, 0.04);
+  /* Full value + ratio, e.g. 9,036 (0.76×) — never ellipsize */
+  overflow: visible;
+  text-overflow: clip;
+  white-space: nowrap;
+  font-size: 0.78rem;
+}
+
+#serializer-metrics-table.compare-matrix-table td:first-child {
+  position: sticky;
+  left: 0;
+  z-index: 2;
+  background: var(--bg-surface);
+  max-width: 14rem;
+}
+
+/* Override older loose header rules that caused interleaved wraps */
+#serializer-metrics-table th {
+  white-space: normal;
+  max-width: none;
+}
+
+.metrics-preset-row {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 0.3rem;
+}
+
+.preset-btn {
+  appearance: none;
+  border: 1px solid var(--border-color);
+  background: var(--bg-surface);
+  color: var(--text-secondary);
+  font-family: var(--font-family);
+  font-size: 0.75rem;
+  font-weight: 500;
+  padding: 0.28rem 0.55rem;
+  border-radius: 999px;
+  cursor: pointer;
+}
+
+.preset-btn:hover {
+  background: #f1f3f4;
+  color: var(--text-primary);
+}
+
+.preset-btn.active {
+  background: var(--bg-blue-light);
+  border-color: #c6dafc;
+  color: var(--color-blue);
+}
+
+.metrics-panel-body {
+  margin-top: 0.5rem;
+  padding-top: 0.5rem;
+  border-top: 1px solid var(--border-color);
+  max-height: 280px;
+  overflow-y: auto;
+}
+
+.metrics-checklist-accordion {
+  display: flex;
+  flex-direction: column;
+  gap: 0.15rem;
+  max-height: none;
+}
+
+.metric-accordion-group {
+  border: 1px solid var(--border-color);
+  border-radius: 6px;
+  background: var(--bg-surface);
+  overflow: hidden;
+}
+
+.metric-accordion-head {
+  display: flex;
+  align-items: center;
+  justify-content: space-between;
+  width: 100%;
+  padding: 0.45rem 0.65rem;
+  border: none;
+  background: transparent;
+  cursor: pointer;
+  font-family: var(--font-family);
+  font-size: 0.78rem;
+  font-weight: 600;
+  color: var(--text-secondary);
+  text-align: left;
+}
+
+.metric-accordion-head:hover {
+  background: #f1f3f4;
+}
+
+.metric-accordion-head .acc-count {
+  font-weight: 500;
+  color: var(--text-muted);
+  font-size: 0.72rem;
+}
+
+.metric-accordion-body {
+  display: none;
+  padding: 0.15rem 0.5rem 0.45rem;
+  border-top: 1px solid var(--border-color);
+}
+
+.metric-accordion-group.open .metric-accordion-body {
+  display: flex;
+  flex-direction: column;
+  gap: 0.1rem;
+}
+
+.metric-accordion-group.open .metric-accordion-head .acc-chevron {
+  transform: rotate(90deg);
+}
+
+.acc-chevron {
+  display: inline-block;
+  transition: transform 0.12s ease;
+  margin-right: 0.35rem;
+  color: var(--text-muted);
+}
+
+.metrics-check-item {
+  display: flex;
+  align-items: center;
+  gap: 0.4rem;
+  font-size: 0.8rem;
+  padding: 0.2rem 0.25rem;
+  cursor: pointer;
+  border-radius: 4px;
+}
+
+.metrics-check-item:hover {
+  background: #f8f9fa;
+}
+
+.compare-table-wrap {
+  margin-top: 0.25rem;
+}
+
+/* Hide dual-column metrics grid leftovers when used in compare */
+.comparison-section .metrics-detail-controls-wide {
+  display: none;
+}
+
+@media (max-width: 720px) {
+  .chip-lang-label {
+    flex-basis: 100%;
+  }
+  .compare-add-select-wrap {
+    max-width: none;
+    flex-basis: 100%;
+  }
+}
+
+/* --- Compare ultra-dense toolbar --- */
+.comparison-section {
+  padding: 0.75rem;
+}
+
+.compare-controls-compact {
+  gap: 0.25rem;
+  margin-bottom: 0.4rem;
+  padding: 0.35rem 0.45rem;
+}
+
+.compare-h2 {
+  font-size: 0.95rem !important;
+  margin: 0 !important;
+  white-space: nowrap;
+}
+
+.compare-ctrl-row-main {
+  flex-wrap: nowrap;
+  gap: 0.35rem 0.45rem;
+  overflow-x: auto;
+}
+
+.compare-ctrl-row-main .compare-status-line {
+  margin-left: auto;
+  white-space: nowrap;
+  font-size: 0.75rem;
+}
+
+.compare-copy-btn {
+  flex-shrink: 0;
+}
+
+/* Selected row: [add controls] [chips scroll] [actions] — no vertical stack */
+.compare-ctrl-row-selected {
+  display: grid;
+  grid-template-columns: auto minmax(0, 1fr) auto;
+  align-items: center;
+  column-gap: 0.4rem;
+  row-gap: 0;
+  padding-top: 0.25rem;
+  min-height: 2rem;
+  flex-wrap: nowrap;
+}
+
+.compare-ctrl-row-selected .compare-inline-add {
+  grid-column: 1;
+  flex: none;
+  width: auto;
+  max-width: none;
+}
+
+.compare-ctrl-row-selected .chip-groups-compact {
+  grid-column: 2;
+  flex: none;
+  width: auto;
+  min-width: 0;
+  max-height: none;
+  height: 1.75rem;
+  display: flex;
+  flex-direction: row;
+  flex-wrap: nowrap;
+  align-items: center;
+  overflow-x: auto;
+  overflow-y: hidden;
+  -webkit-overflow-scrolling: touch;
+}
+
+.compare-ctrl-row-selected .compare-sel-actions {
+  grid-column: 3;
+}
+
+.compare-ctrl-row-selected .chip-groups-compact .xl-chip {
+  display: inline-flex;
+  flex-shrink: 0;
+  font-size: 0.68rem;
+  padding: 0.05rem 0.15rem 0.05rem 0.35rem;
+  max-width: 9rem;
+}
+
+.compare-ctrl-row-selected .chip-groups-compact .xl-chip-label {
+  max-width: 7rem;
+}
+
+/* When same-panel is shown, same grid applies */
+#compare-same-panel.compare-inline-add {
+  flex-direction: row;
+  flex-wrap: nowrap;
+  width: auto;
+  align-items: center;
+}
+
+#compare-same-panel .same-lang-wrap {
+  flex: 0 0 auto;
+}
+
+#compare-same-panel #same-lang-select {
+  width: 5.5rem;
+  max-width: 5.5rem;
+  min-width: 5.5rem;
+  font-size: 0.78rem;
+  padding: 0.25rem 1.35rem 0.25rem 0.4rem;
+}
+
+#compare-same-filters .select-wrapper select {
+  max-width: 12rem;
+}
+
+.compare-ctrl-row-metrics {
+  flex-wrap: nowrap;
+  gap: 0.3rem 0.4rem;
+  padding-top: 0.25rem;
+  overflow-x: auto;
+}
+
+.compare-xl-hint {
+  margin: 0;
+  padding: 0;
+  font-size: 0.7rem;
+  color: #8a6d00;
+  line-height: 1.2;
+}
+
+#xl-add-panel #xl-add-lang {
+  max-width: 5.5rem;
+  min-width: 4rem;
+  font-size: 0.78rem;
+  padding: 0.25rem 1.4rem 0.25rem 0.4rem;
+}
+
+#xl-add-panel .xl-add-ser-wrap {
+  flex: 0 1 11rem;
+  max-width: 12rem;
+  min-width: 7rem;
+}
+
+.compare-lab-filters-inline .select-wrapper select {
+  max-width: 12rem;
+  font-size: 0.78rem;
+  padding: 0.25rem 1.4rem 0.25rem 0.4rem;
+}
+
+.comparison-section .glass-panel,
+.comparison-section.glass-panel {
+  /* section itself is glass-panel */
+}
diff --git a/dashboard/index.html b/dashboard/index.html
index 764f22fa..23c515a5 100644
--- a/dashboard/index.html
+++ b/dashboard/index.html
@@ -8,24 +8,33 @@
   <link rel="icon" href="./favicon.svg" type="image/svg+xml">
   <link rel="stylesheet" href="./index.css">
   <!-- Chart.js from CDN -->
-  <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
+  <script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.1/dist/chart.umd.min.js"></script>
 </head>
 <body>
 
   <header>
-    <div class="logo">
-      <div class="logo-icon">📊</div>
-      <h1>Serializer Analytics dashboard</h1>
+    <div class="header-bar">
+      <div class="logo">
+        <div class="logo-icon" aria-hidden="true">
+          <svg width="20" height="20" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><path d="M3 3v18h18"/><path d="M7 14l4-4 4 4 5-6"/></svg>
+        </div>
+        <h1>Serializer Analytics Dashboard</h1>
+      </div>
+      <button type="button" id="nav-toggle" class="nav-toggle" aria-label="Open navigation" aria-expanded="false" aria-controls="main-nav">
+        <span class="nav-toggle-bar"></span>
+        <span class="nav-toggle-bar"></span>
+        <span class="nav-toggle-bar"></span>
+      </button>
     </div>
-    <ul class="nav-links">
-      <li><a href="../" id="nav-docs-link" style="margin-right: 0.75rem; border: 1px solid var(--border-color); font-weight: 500;">← Back to Docs</a></li>
-      <li class="active"><a href="#dashboard" id="nav-dash-link">Dashboard</a></li>
-      <li><a href="#detailed-analytics" id="nav-table-link">Details</a></li>
-      <li><a href="#compare" id="nav-compare-link">Compare</a></li>
-      <li><a href="#cross-lang" id="nav-cross-link">Cross-lang</a></li>
-      <li><a href="#serializer-metrics" id="nav-metrics-link">All Metrics</a></li>
-      <li><a href="#history-custom" id="nav-history-link">History</a></li>
-    </ul>
+    <nav id="main-nav" class="main-nav" aria-label="Dashboard sections">
+      <ul class="nav-links">
+        <li><a href="../" id="nav-docs-link" class="nav-docs">← Back to Docs</a></li>
+        <li class="active"><a href="#dashboard" id="nav-dash-link">Dashboard</a></li>
+        <li><a href="#detailed-analytics" id="nav-table-link">Details</a></li>
+        <li><a href="#compare" id="nav-compare-link">Compare</a></li>
+        <li><a href="#history-custom" id="nav-history-link">History</a></li>
+      </ul>
+    </nav>
   </header>
 
   <main class="container">
@@ -62,6 +71,16 @@ <h1>Serializer Analytics dashboard</h1>
             <!-- Dynamically populated -->
           </select>
         </div>
+
+        <span class="filter-label" title="Which sample set feeds tables, charts, and Pareto">Samples:</span>
+        <div class="select-wrapper">
+          <select id="filter-policy-select" aria-label="Sample filter policy for aggregations">
+            <option value="iqr_1.5">IQR k=1.5 (default)</option>
+            <option value="all">All trials</option>
+            <option value="iqr_3">IQR k=3 (loose)</option>
+            <option value="winsorize_5_95">Winsorize 5–95%</option>
+          </select>
+        </div>
       </div>
 
       <div class="tabs">
@@ -70,27 +89,35 @@ <h1>Serializer Analytics dashboard</h1>
       </div>
     </section>
 
+    <div id="filter-policy-meta" class="filter-policy-meta glass-panel" hidden>
+      <span id="filter-policy-meta-text" class="filter-policy-meta-text"></span>
+    </div>
+
+    <div id="run-meta" class="run-meta glass-panel" hidden>
+      <span id="run-meta-text" class="run-meta-text"></span>
+    </div>
+
     <!-- KPI Summary Cards -->
-    <section class="summary-grid">
+    <section class="summary-grid" aria-live="polite">
       <div class="glass-panel kpi-card">
         <span class="kpi-title">Tested Libraries</span>
-        <span class="kpi-value" id="kpi-total">-</span>
+        <span class="kpi-value" id="kpi-total">Loading…</span>
         <span class="kpi-desc">Total serializers in this workload</span>
       </div>
-      <div class="glass-panel kpi-card purple">
+      <div class="glass-panel kpi-card featured">
         <span class="kpi-title">Fastest Serializer</span>
-        <span class="kpi-value" id="kpi-fastest" style="font-size: 1.5rem; line-height: 2.2rem;">-</span>
-        <span class="kpi-desc" id="kpi-fastest-val">Speed: -</span>
+        <span class="kpi-value kpi-value-name" id="kpi-fastest">Loading…</span>
+        <span class="kpi-desc" id="kpi-fastest-val">Waiting for data</span>
       </div>
       <div class="glass-panel kpi-card green">
         <span class="kpi-title">Most Compact</span>
-        <span class="kpi-value" id="kpi-compact" style="font-size: 1.5rem; line-height: 2.2rem;">-</span>
-        <span class="kpi-desc" id="kpi-compact-val">Size: -</span>
+        <span class="kpi-value kpi-value-name" id="kpi-compact">Loading…</span>
+        <span class="kpi-desc" id="kpi-compact-val">Waiting for data</span>
       </div>
       <div class="glass-panel kpi-card">
         <span class="kpi-title">Pareto Frontier</span>
-        <span class="kpi-value" id="kpi-pareto">-</span>
-        <span class="kpi-desc">Optimal trade-offs (Speed/Size)</span>
+        <span class="kpi-value" id="kpi-pareto">Loading…</span>
+        <span class="kpi-desc">Optimal trade-offs (speed / size)</span>
       </div>
     </section>
 
@@ -99,7 +126,11 @@ <h1>Serializer Analytics dashboard</h1>
       <div class="glass-panel">
         <div class="chart-header">
           <h2 class="chart-title">Speed vs Size Trade-off</h2>
-          <span class="badge badge-cyan" id="scatter-badge">Pareto Front Highlighted</span>
+          <div class="chart-toolbar">
+            <span class="badge badge-cyan" id="scatter-badge">Pareto front</span>
+            <button type="button" id="btn-chart-log" class="tab-btn chart-tool-btn" title="Toggle log scale on scatter X axis">Log X</button>
+            <button type="button" id="btn-export-scatter" class="tab-btn chart-tool-btn" title="Download scatter PNG">PNG</button>
+          </div>
         </div>
         <div class="chart-container">
           <canvas id="scatter-chart"></canvas>
@@ -108,204 +139,185 @@ <h2 class="chart-title">Speed vs Size Trade-off</h2>
 
       <div class="glass-panel">
         <div class="chart-header">
-          <h2 class="chart-title">Performance Comparison</h2>
+          <h2 class="chart-title" id="bar-chart-title">Throughput &amp; Size Ranking</h2>
+          <div class="chart-toolbar">
+            <span class="filter-label" style="margin:0;">Sort</span>
+            <button type="button" id="btn-rank-sort-size" class="tab-btn chart-tool-btn" title="Sort by median size (compact first)">Size</button>
+            <button type="button" id="btn-rank-sort-speed" class="tab-btn chart-tool-btn active" title="Sort by ops/s (highest first)">Ops/s</button>
+            <button type="button" id="btn-export-bar" class="tab-btn chart-tool-btn" title="Download ranking PNG">PNG</button>
+          </div>
         </div>
-        <div class="chart-container">
+        <p class="section-help ranking-help" id="ranking-help">
+          Single diverging chart:
+          <span class="rank-legend-size">◀ size</span> left ·
+          <span class="rank-legend-speed">ops/s ▶</span> right.
+          Each side is normalized to the chart max (100); hover for absolute values.
+        </p>
+        <div class="chart-container ranking-chart-single">
           <canvas id="bar-chart"></canvas>
         </div>
       </div>
     </section>
 
-    <!-- Detailed Analytics Table -->
+    <!-- Detailed Analytics Table (full roster) -->
     <section class="glass-panel table-panel" id="detailed-analytics">
       <div class="table-header-row">
-        <h2 class="chart-title">Detailed Analytics</h2>
-        <div class="search-input-wrapper">
-          <input type="text" id="table-search" class="search-input" placeholder="Search serializers..." aria-label="Search serializers">
+        <div>
+          <h2 class="chart-title">Detailed Analytics</h2>
+          <p class="section-help" id="detailed-analytics-help">
+            Roster with Median / Std / P95 / P99 for speed or latency, plus median size.
+            Pareto-optimal rows are highlighted. Cells: <code>value (ratio×)</code> vs baseline.
+          </p>
+        </div>
+        <div class="table-header-actions">
+          <div class="tabs roster-metric-tabs" role="tablist" aria-label="Detailed Analytics speed metric">
+            <button type="button" class="tab-btn active" id="btn-roster-ops">Ops/s</button>
+            <button type="button" class="tab-btn" id="btn-roster-latency">Latency</button>
+          </div>
+          <label class="filter-label" for="roster-baseline-select" style="margin:0;">Baseline</label>
+          <div class="select-wrapper">
+            <select id="roster-baseline-select" aria-label="Roster baseline serializer"></select>
+          </div>
+          <button type="button" id="btn-copy-roster-md" class="tab-btn" style="font-size:0.8rem;">Copy Markdown</button>
+          <div class="search-input-wrapper">
+            <input type="text" id="table-search" class="search-input" placeholder="Search serializers…" aria-label="Search serializers">
+          </div>
         </div>
       </div>
 
       <div class="table-container">
-        <table id="analytics-table">
+        <table id="analytics-table" class="data-table view-ops">
           <thead>
             <tr>
-              <th id="th-serializer" class="sort-asc">Serializer</th>
-              <th id="th-ops">Ops/Sec</th>
-              <th id="th-total-ns">Total Latency</th>
-              <th id="th-ser-ns">Ser Latency</th>
-              <th id="th-deser-ns">Deser Latency</th>
-              <th id="th-size">Median Size (Bytes)</th>
-              <th id="th-optimal">Optimal</th>
+              <th id="th-serializer" class="str sort-asc">Serializer</th>
+              <!-- Ops/s stats (shown when roster view = ops) -->
+              <th id="th-ops-median" class="num roster-col-ops">Median</th>
+              <th id="th-ops-std" class="num roster-col-ops">Std</th>
+              <th id="th-ops-p95" class="num roster-col-ops">P95</th>
+              <th id="th-ops-p99" class="num roster-col-ops">P99</th>
+              <!-- Latency stats (shown when roster view = latency) -->
+              <th id="th-lat-median" class="num roster-col-latency">Median</th>
+              <th id="th-lat-std" class="num roster-col-latency">Std</th>
+              <th id="th-lat-p95" class="num roster-col-latency">P95</th>
+              <th id="th-lat-p99" class="num roster-col-latency">P99</th>
+              <th id="th-size" class="num">Median size (bytes)</th>
             </tr>
           </thead>
-          <tbody id="table-body">
-            <!-- Dynamically populated -->
-          </tbody>
+          <tbody id="table-body"></tbody>
         </table>
       </div>
     </section>
 
-    <!-- Serializer Comparison Matrix -->
+    <!-- Unified Compare lab -->
     <section class="glass-panel comparison-section" id="compare">
-      <div class="chart-header">
-        <h2 class="chart-title">Side-by-Side Comparison</h2>
-      </div>
-
-      <div class="compare-pickers">
-        <div class="picker-card">
-          <label for="compare-a-select" class="filter-label">Serializer A (Reference)</label>
-          <div class="select-wrapper">
-            <select id="compare-a-select" style="width: 100%;">
-              <!-- Populated dynamically -->
-            </select>
-          </div>
-        </div>
-        <div class="picker-card">
-          <label for="compare-b-select" class="filter-label">Serializer B (Target)</label>
-          <div class="select-wrapper">
-            <select id="compare-b-select" style="width: 100%;">
-              <!-- Populated dynamically -->
-            </select>
+      <!-- Dense 2-row toolbar + optional metrics panel -->
+      <div class="compare-controls-compact">
+        <div class="compare-ctrl-row compare-ctrl-row-main">
+          <h2 class="chart-title compare-h2">Compare</h2>
+          <div class="compare-scope-tabs tabs" role="tablist">
+            <button type="button" class="tab-btn active" id="btn-compare-same" data-scope="same">Same language</button>
+            <button type="button" class="tab-btn" id="btn-compare-xl" data-scope="cross">Cross-language</button>
           </div>
-        </div>
-      </div>
-
-      <div class="compare-grid">
-        <div class="glass-panel compare-card">
-          <span class="compare-metric">Total Latency</span>
-          <span class="compare-value" id="compare-total-val">-</span>
-          <span class="compare-diff" id="compare-total-diff">-</span>
-        </div>
-        <div class="glass-panel compare-card">
-          <span class="compare-metric">Serialization</span>
-          <span class="compare-value" id="compare-ser-val">-</span>
-          <span class="compare-diff" id="compare-ser-diff">-</span>
-        </div>
-        <div class="glass-panel compare-card">
-          <span class="compare-metric">Deserialization</span>
-          <span class="compare-value" id="compare-deser-val">-</span>
-          <span class="compare-diff" id="compare-deser-diff">-</span>
-        </div>
-        <div class="glass-panel compare-card">
-          <span class="compare-metric">Throughput</span>
-          <span class="compare-value" id="compare-throughput-val">-</span>
-          <span class="compare-diff" id="compare-throughput-diff">-</span>
-        </div>
-        <div class="glass-panel compare-card">
-          <span class="compare-metric">Serialized Size</span>
-          <span class="compare-value" id="compare-size-val">-</span>
-          <span class="compare-diff" id="compare-size-diff">-</span>
-        </div>
-      </div>
-    </section>
+          <span class="badge badge-slate" id="compare-scope-badge" hidden>Same language</span>
 
-    <!-- Cross-language side-by-side comparison -->
-    <section class="glass-panel cross-lang-section" id="cross-lang">
-      <div class="chart-header">
-        <h2 class="chart-title">Cross-language Comparison</h2>
-        <span class="badge badge-purple" id="cross-lang-badge">Pareto best by default</span>
-      </div>
-      <p class="section-help">
-        Compare serializers across languages for the same workload. Default selection is each language’s
-        <strong>Pareto-best</strong> set (speed vs size), limited to
-        <strong>at most 2 per language</strong> (fastest first) so the diagram stays readable.
-        Add or remove any language/serializer pair.
-      </p>
-
-      <div class="cross-lang-filters">
-        <div class="filter-group" style="flex-wrap: wrap;">
-          <span class="filter-label">Test Data:</span>
-          <div class="select-wrapper">
-            <select id="xl-data-select" aria-label="Cross-language test data"></select>
+          <div class="filter-group compare-lab-filters-inline" id="compare-same-filters">
+            <span class="filter-label">Test Data</span>
+            <div class="select-wrapper">
+              <select id="same-data-select" aria-label="Same-language test data"></select>
+            </div>
+            <span class="filter-label">Mode</span>
+            <div class="select-wrapper">
+              <select id="same-mode-select" aria-label="Same-language mode"></select>
+            </div>
+            <span class="filter-label">Baseline</span>
+            <div class="select-wrapper">
+              <select id="compare-baseline-select" aria-label="Baseline serializer"></select>
+            </div>
           </div>
-          <span class="filter-label">Mode:</span>
-          <div class="select-wrapper">
-            <select id="xl-mode-select" aria-label="Cross-language mode"></select>
+
+          <div class="filter-group compare-lab-filters-inline" id="compare-xl-filters" hidden>
+            <span class="filter-label">Test Data</span>
+            <div class="select-wrapper">
+              <select id="xl-data-select" aria-label="Cross-language test data"></select>
+            </div>
+            <span class="filter-label">Mode</span>
+            <div class="select-wrapper">
+              <select id="xl-mode-select" aria-label="Cross-language mode"></select>
+            </div>
+            <span class="filter-label">Baseline</span>
+            <div class="select-wrapper">
+              <select id="compare-xl-baseline-select" aria-label="Cross-language baseline"></select>
+            </div>
           </div>
-          <button type="button" id="xl-reset-pareto" class="tab-btn active" style="font-size: 0.85rem;"
-            title="Re-select up to 2 Pareto-optimal serializers per language (fastest first)">
-            Reset to Pareto best
-          </button>
-        </div>
-      </div>
 
-      <div class="cross-lang-add-row">
-        <div class="select-wrapper">
-          <select id="xl-add-lang" aria-label="Language to add"></select>
-        </div>
-        <div class="select-wrapper xl-add-ser-wrap">
-          <select id="xl-add-serializer" aria-label="Serializer to add"></select>
+          <span class="compare-status-line" id="compare-status-line">0 serializers · 0 metrics</span>
+          <button type="button" id="btn-copy-compare-md" class="tab-btn chart-tool-btn compare-copy-btn">Copy Markdown</button>
         </div>
-        <button type="button" id="xl-add-btn" class="tab-btn xl-add-btn">
-          Add
-        </button>
-      </div>
 
-      <div id="xl-selection-chips" class="xl-chips" aria-label="Selected serializers for comparison">
-        <!-- chips populated dynamically -->
-      </div>
-
-      <div class="table-container xl-table-wrap">
-        <table id="xl-compare-table">
-          <thead id="xl-compare-head">
-            <tr><th>Metric</th></tr>
-          </thead>
-          <tbody id="xl-compare-body">
-            <!-- populated dynamically -->
-          </tbody>
-        </table>
-      </div>
-    </section>
-
-    <!-- Multi-serializer full metrics (grouped) -->
-    <section class="glass-panel metrics-detail-section" id="serializer-metrics">
-      <div class="chart-header">
-        <h2 class="chart-title">All Metrics</h2>
-      </div>
-      <p class="section-help">
-        Compare full metric sets for one or more serializers under the current language / test data / mode.
-        Metrics are grouped by family; use the checklists to show only what you need.
-      </p>
+        <div class="compare-ctrl-row compare-ctrl-row-selected">
+          <div id="compare-same-panel" class="compare-inline-add">
+            <div class="select-wrapper same-lang-wrap">
+              <select id="same-lang-select" aria-label="Language for comparison"></select>
+            </div>
+            <input type="search" id="same-ser-search" class="compare-search-input" placeholder="Filter…" aria-label="Filter serializers to add" autocomplete="off">
+            <div class="select-wrapper compare-add-select-wrap">
+              <select id="same-ser-add-select" aria-label="Serializer to add"></select>
+            </div>
+            <button type="button" id="same-ser-add-btn" class="tab-btn chart-tool-btn">Add</button>
+          </div>
 
-      <div class="metrics-detail-controls metrics-detail-controls-wide">
-        <div class="picker-card metrics-checklist-card">
-          <div class="metrics-checklist-header">
-            <span class="filter-label">Serializers</span>
-            <div class="metrics-checklist-actions">
-              <button type="button" id="detail-ser-select-all" class="link-btn">All</button>
-              <button type="button" id="detail-ser-select-none" class="link-btn">None</button>
+          <div id="xl-add-panel" class="compare-inline-add xl-add-panel" hidden>
+            <div class="select-wrapper xl-lang-wrap">
+              <select id="xl-add-lang" aria-label="Language to add"></select>
+            </div>
+            <div class="select-wrapper xl-add-ser-wrap">
+              <select id="xl-add-serializer" aria-label="Serializer to add"></select>
             </div>
+            <button type="button" id="xl-add-btn" class="tab-btn chart-tool-btn">Add</button>
           </div>
-          <div id="detail-serializer-checklist" class="metrics-checklist serializers-checklist" role="group" aria-label="Serializer checklist">
-            <!-- Populated dynamically -->
+
+          <div id="same-selection-chips" class="chip-groups chip-groups-compact" aria-label="Selected serializers"></div>
+          <div id="xl-selection-chips" class="chip-groups chip-groups-compact" hidden aria-label="Selected serializers for comparison"></div>
+
+          <div class="metrics-checklist-actions compare-sel-actions">
+            <button type="button" id="xl-reset-pareto" class="link-btn" hidden title="Up to 2 Pareto-optimal per language">Pareto</button>
+            <button type="button" id="detail-ser-select-none" class="link-btn">Clear</button>
+            <button type="button" id="detail-ser-select-all" class="link-btn">All</button>
           </div>
         </div>
 
-        <div class="picker-card metrics-checklist-card">
-          <div class="metrics-checklist-header">
-            <span class="filter-label">Show metrics</span>
-            <div class="metrics-checklist-actions">
-              <button type="button" id="metrics-select-all" class="link-btn">All</button>
-              <button type="button" id="metrics-select-none" class="link-btn">None</button>
-              <button type="button" id="metrics-select-default" class="link-btn">Defaults</button>
-            </div>
+        <div class="compare-ctrl-row compare-ctrl-row-metrics">
+          <span class="filter-label">Metrics</span>
+          <span class="badge badge-slate" id="metrics-selected-count">0</span>
+          <div class="metrics-preset-row" role="group" aria-label="Metric presets">
+            <button type="button" class="preset-btn active" data-preset="defaults" id="metrics-select-default">Defaults</button>
+            <button type="button" class="preset-btn" data-preset="latency" id="metrics-preset-latency">Latency</button>
+            <button type="button" class="preset-btn" data-preset="size" id="metrics-preset-size">Size</button>
+            <button type="button" class="preset-btn" data-preset="custom" id="metrics-edit-toggle">Custom ▾</button>
           </div>
-          <div id="metrics-checklist" class="metrics-checklist metrics-checklist-grouped" role="group" aria-label="Metric checklist by group">
-            <!-- Populated dynamically, grouped -->
+          <div class="metrics-checklist-actions">
+            <button type="button" id="metrics-select-all" class="link-btn">All</button>
+            <button type="button" id="metrics-select-none" class="link-btn">None</button>
           </div>
+          <span id="compare-selected-count" class="badge badge-slate" hidden>0</span>
         </div>
+        <div id="metrics-panel-body" class="metrics-panel-body" hidden>
+          <div id="metrics-checklist" class="metrics-checklist metrics-checklist-accordion" role="group" aria-label="Metric checklist by group"></div>
+        </div>
+
+        <p id="compare-xl-disclaimer" class="compare-xl-hint" hidden title="Runtimes, GCs, and hosts differ">
+          Cross-lang times are directional only
+        </p>
+
+        <div id="detail-serializer-checklist" hidden></div>
       </div>
 
-      <div class="table-container xl-table-wrap">
-        <table id="serializer-metrics-table">
+      <div class="table-container xl-table-wrap compare-table-wrap">
+        <table id="serializer-metrics-table" class="data-table compare-matrix-table">
           <thead id="serializer-metrics-head">
-            <tr>
-              <th>Metric</th>
-            </tr>
+            <tr><th class="str">Metric</th></tr>
           </thead>
-          <tbody id="serializer-metrics-body">
-            <!-- Dynamically populated -->
-          </tbody>
+          <tbody id="serializer-metrics-body"></tbody>
         </table>
       </div>
     </section>
@@ -313,46 +325,44 @@ <h2 class="chart-title">All Metrics</h2>
     <!-- History & Custom Runs Section -->
     <section class="glass-panel" id="history-custom">
       <div class="chart-header">
-        <h2 class="chart-title">History & Custom Runs</h2>
+        <h2 class="chart-title">History &amp; Custom Runs</h2>
       </div>
+      <p class="section-help">Load a past run from local logs (dev server) or upload a stats JSON file (works on GitHub Pages too).</p>
 
       <div class="compare-pickers">
-        <!-- Historical Runs Downloader (Local Logs) -->
-        <div class="picker-card" style="gap: 1rem;">
-          <h3 class="filter-label" style="color: var(--accent-cyan); font-size: 1rem;">Historical Runs (Local Logs)</h3>
-          <p style="font-size: 0.9rem; color: var(--text-secondary);">
-            Access run results stored in the local logs folder. Select a run timestamp to download raw files or inspect them.<br>
-            <span style="font-size: 0.8rem; color: var(--text-muted); font-style: italic;">*Note: Historical log file downloads require a local dashboard installation.</span>
+        <div class="picker-card utility-card">
+          <h3 class="utility-card-title">Historical Runs</h3>
+          <p class="section-help" id="history-local-note">
+            Select a run timestamp to download raw files or inspect them. Requires a local logs tree.
+          </p>
+          <p class="section-help" id="history-pages-note" hidden>
+            Raw log downloads are unavailable on the static site. Use <strong>Upload Custom Stats</strong> or the packed latest data.
           </p>
-          
           <div style="display: flex; flex-direction: column; gap: 0.5rem;">
-            <label for="history-run-select" class="filter-label">Available Runs:</label>
+            <label for="history-run-select" class="filter-label">Available runs</label>
             <div class="select-wrapper">
               <select id="history-run-select" style="width: 100%;">
-                <option value="">-- No runs loaded --</option>
+                <option value="">— No runs loaded —</option>
               </select>
             </div>
           </div>
-
-          <div style="display: grid; grid-template-columns: repeat(2, 1fr); gap: 0.75rem; margin-top: 0.5rem;">
-            <button id="download-csv-btn" class="tab-btn" style="border: 1px solid var(--panel-border); font-size: 0.85rem;" disabled>Download CSV</button>
-            <button id="download-config-btn" class="tab-btn" style="border: 1px solid var(--panel-border); font-size: 0.85rem;" disabled>Download Config</button>
-            <button id="download-error-btn" class="tab-btn" style="border: 1px solid var(--panel-border); font-size: 0.85rem;" disabled>Download Errors</button>
+          <div class="utility-actions">
+            <button id="download-csv-btn" class="tab-btn" style="font-size: 0.85rem;" disabled>Download CSV</button>
+            <button id="download-config-btn" class="tab-btn" style="font-size: 0.85rem;" disabled>Download Config</button>
+            <button id="download-error-btn" class="tab-btn" style="font-size: 0.85rem;" disabled>Download Errors</button>
             <button id="load-history-btn" class="tab-btn active" style="font-size: 0.85rem;" disabled>Load to Inspect</button>
           </div>
         </div>
 
-        <!-- Custom Run Upload -->
-        <div class="picker-card" style="gap: 1rem;">
-          <h3 class="filter-label" style="color: var(--accent-purple); font-size: 1rem;">Upload Custom Stats</h3>
-          <p style="font-size: 0.9rem; color: var(--text-secondary);">
-            Drag and drop a custom computed stats JSON file (e.g. <code>stats_*.json</code>) from your local system to load it instantly.
-          </p>
-
-          <div id="drop-zone" class="dropzone" style="padding: 1.5rem 1rem;">
-            <span class="dropzone-icon" style="font-size: 2rem;">📥</span>
-            <h4 style="font-size: 0.95rem;">Drag & Drop custom stats JSON file here</h4>
-            <p style="font-size: 0.8rem; color: var(--text-muted);">Or click to browse and upload</p>
+        <div class="picker-card utility-card">
+          <h3 class="utility-card-title">Upload Custom Stats</h3>
+          <p class="section-help">Drop a computed stats JSON file (e.g. <code>stats_*.json</code>).</p>
+          <div id="drop-zone" class="dropzone">
+            <span class="dropzone-icon" aria-hidden="true">
+              <svg width="28" height="28" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M21 15v4a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2v-4"/><polyline points="17 8 12 3 7 8"/><line x1="12" y1="3" x2="12" y2="15"/></svg>
+            </span>
+            <h4 style="font-size: 0.95rem;">Drag &amp; drop stats JSON</h4>
+            <p style="font-size: 0.8rem; color: var(--text-muted);">Or click to browse</p>
             <input type="file" id="file-input" style="display: none;" accept=".json">
           </div>
           <div id="upload-status" style="font-weight: 500; text-align: center; font-size: 0.9rem; display: none;"></div>
diff --git a/dashboard/main.js b/dashboard/main.js
index 93fa5bf5..3c74817c 100644
--- a/dashboard/main.js
+++ b/dashboard/main.js
@@ -1,20 +1,81 @@
-import { initCharts, updateCharts } from './charts.js';
-
-const SETTINGS_KEY = 'serializer-dashboard-settings-v1';
-
-/** Keys that identify a group, not metrics. */
-const GROUP_META_KEYS = new Set(['serializer', 'test_data', 'mode', 'language']);
-
-/** Suite fixture base type ids. */
-const SUITE_TYPE_IDS = ['message', 'document', 'telemetry', 'strings', 'event'];
-
 /**
- * Display / filter key: "message@n=1" when batch axis is present.
- * Idempotent: safe if test_data is already labeled (or even doubled like "x@n=1@n=1").
+ * Dashboard UI terminology: always say **data type** (test_data / Test Data control).
+ * Never use "fixture" in user-visible copy, notifications, KPIs, or export notes.
+ * Internal helpers may still say fixture* in identifiers until renamed.
  */
+import {
+  initCharts,
+  updateCharts,
+  setChartLogScale,
+  getChartLogScale,
+  setRankSort,
+  getRankSort,
+  exportScatterPng,
+  exportBarPng,
+} from './charts.js';
+import {
+  formatSig,
+  formatIntGrouped,
+  formatMetricCell,
+  formatRelativeCell,
+  scalesFromGroups,
+  metricHeaderLabel,
+  metricKind,
+  formatOpsCompact,
+  formatTimeCompact,
+  formatOpsCell,
+  chooseLatencyUnit,
+  chooseOpsUnit,
+  serializerLabelFromGroup,
+} from './format.js';
+
+const SETTINGS_KEY = 'serializer-dashboard-settings-v2';
+
+const GROUP_META_KEYS = new Set([
+  'serializer',
+  'test_data',
+  'mode',
+  'language',
+  'filter',
+  'variants',
+  'serializer_version',
+  'type_config_hash',
+  'StreamMode',
+  'compounded',
+  'compound_parts',
+]);
+const SUITE_TYPE_IDS = ['message', 'document', 'telemetry', 'strings', 'event'];
+
+/** Named sample-filter policies (must match analysis FILTER_POLICY_IDS). */
+const FILTER_POLICY_FALLBACK = {
+  all: {
+    id: 'all',
+    label: 'All trials (post-warmup)',
+    description:
+      'Every measured repetition after warmup. No IQR drop and no winsorization.',
+  },
+  'iqr_1.5': {
+    id: 'iqr_1.5',
+    label: 'IQR k=1.5 (strict / default)',
+    description:
+      'Paired Tukey fences (k=1.5) on ser/deser/total; drop if outlier on any.',
+  },
+  iqr_3: {
+    id: 'iqr_3',
+    label: 'IQR k=3 (loose)',
+    description: 'Same paired IQR rule with k=3 (only extreme stalls removed).',
+  },
+  winsorize_5_95: {
+    id: 'winsorize_5_95',
+    label: 'Winsorize 5–95%',
+    description: 'Clip ser/deser/total at 5th–95th percentiles; n unchanged.',
+  },
+};
+const DEFAULT_FILTER_POLICY = 'iqr_1.5';
+const FILTER_POLICY_ORDER = ['all', 'iqr_1.5', 'iqr_3', 'winsorize_5_95'];
+
 function fixtureKey(g) {
   const raw = String(g?.test_data ?? '');
-  // Strip one or more trailing @n=<int> segments so re-labeling never stacks.
   const base = raw.replace(/(@n=\d+)+$/i, '') || raw;
   let n = g?.data_type_instance_count;
   if (n == null || n === '') {
@@ -29,12 +90,10 @@ function fixtureKey(g) {
 
 function baseTypeId(key) {
   if (!key) return '';
-  // First @n= starts the batch suffix (handles accidental doubles).
   const i = String(key).indexOf('@n=');
   return i >= 0 ? String(key).slice(0, i) : String(key);
 }
 
-/** Prefer message@n=1, then message, then any suite type. */
 function pickPreferredFixture(options) {
   if (!options || !options.length) return '';
   const preferred = [];
@@ -45,10 +104,9 @@ function pickPreferredFixture(options) {
     if (options.includes(p)) return p;
   }
   const cleaned = options.filter((o) => SUITE_TYPE_IDS.includes(baseTypeId(o)));
-  return (cleaned[0] || options[0] || '');
+  return cleaned[0] || options[0] || '';
 }
 
-
 const LANGUAGE_CATALOG = [
   { id: 'csharp', label: 'C#' },
   { id: 'rust', label: 'Rust' },
@@ -61,106 +119,189 @@ const LANGUAGE_CATALOG = [
   { id: 'swift', label: 'Swift' },
 ];
 
-/** Metrics shown as rows in the cross-language matrix. */
 const CROSS_LANG_METRICS = [
-  { key: 'avg_ops_per_sec', label: 'Ops/Sec', higherIsBetter: true },
-  { key: 'avg_time_total_ns', label: 'Total latency', higherIsBetter: false },
+  { key: 'avg_ops_per_sec', label: 'Ops/s', higherIsBetter: true },
+  { key: 'avg_time_total_ns', label: 'Total latency (mean)', higherIsBetter: false },
   { key: 'avg_time_ser_ns', label: 'Ser latency', higherIsBetter: false },
   { key: 'avg_time_deser_ns', label: 'Deser latency', higherIsBetter: false },
   { key: 'total_median_ns', label: 'Median total', higherIsBetter: false },
+  { key: 'total_p95_ns', label: 'Total p95', higherIsBetter: false },
   { key: 'median_size_bytes', label: 'Median size', higherIsBetter: false },
   { key: 'mean_fidelity', label: 'Fidelity', higherIsBetter: true },
+  { key: 'mean_memory_peak_bytes', label: 'Peak memory', higherIsBetter: false },
   { key: 'runs', label: 'Samples', higherIsBetter: null },
+  { key: 'total_cv', label: 'Total CV', higherIsBetter: false },
 ];
 
-/** Default checklist when no saved selection exists. */
 const DEFAULT_SELECTED_METRICS = [
   'avg_ops_per_sec',
   'avg_time_total_ns',
   'avg_time_ser_ns',
   'avg_time_deser_ns',
   'total_median_ns',
-  'ser_median_ns',
-  'deser_median_ns',
+  'total_p95_ns',
+  'total_ci_low_ns',
+  'total_ci_high_ns',
   'median_size_bytes',
-  'size_median_bytes',
-  'runs',
   'mean_fidelity',
+  'mean_memory_peak_bytes',
+  'runs',
   'serializer_version',
 ];
 
-// State Management
+/** Max serializer columns in Compare matrix (baseline counts). */
+const MAX_COMPARE_COLUMNS = 8;
+
+/** Metric presets for Compare catalog. */
+const METRIC_PRESETS = {
+  defaults: DEFAULT_SELECTED_METRICS,
+  latency: [
+    'avg_time_total_ns',
+    'avg_time_ser_ns',
+    'avg_time_deser_ns',
+    'total_median_ns',
+    'total_p95_ns',
+    'total_p50_ns',
+    'total_p99_ns',
+    'total_ci_low_ns',
+    'total_ci_high_ns',
+    'total_cv',
+    'ser_median_ns',
+    'deser_median_ns',
+  ],
+  size: ['median_size_bytes', 'mean_memory_peak_bytes', 'mean_fidelity', 'runs'],
+};
+
+/** Open metric accordion groups (name -> bool). */
+const metricAccordionOpen = {};
+
 let state = {
   currentLanguage: 'csharp',
   currentTestData: '',
   currentMode: '',
-  displayMetric: 'ops', // 'ops' or 'time'
+  displayMetric: 'ops', // charts / ranking toolbar
+  /** Detailed Analytics only: 'ops' | 'time' (independent of displayMetric). */
+  rosterMetric: 'ops',
+  rankSort: 'speed', // 'speed' | 'size' for ranking chart
   searchQuery: '',
   sortKey: 'serializer',
-  sortDirection: 'asc', // 'asc' or 'desc'
-  allGroups: [], // All serializer runs for the loaded file
-  filteredGroups: [], // Filtered by test_data and mode
-  paretoSerializerNames: [], // Names of Pareto-optimal serializers
-  serializerNames: [], // Names of all serializers in filtered group
-  compareA: '',
-  compareB: '',
-  detailSerializers: [], // multi-select for Serializer Metrics table
-  availableMetrics: [], // all metric field ids in loaded data
+  sortDirection: 'asc',
+  allGroups: [],
+  /** @type {Record<string, object[]>} policy id → full group list for current language */
+  groupsByPolicy: {},
+  /** @type {Record<string, object>} policy catalog from export or fallback */
+  filterPolicies: { ...FILTER_POLICY_FALLBACK },
+  filterPolicy: DEFAULT_FILTER_POLICY,
+  defaultFilterPolicy: DEFAULT_FILTER_POLICY,
+  filteredGroups: [],
+  paretoSerializerNames: [],
+  serializerNames: [],
+  detailSerializers: [],
+  availableMetrics: [],
   selectedMetrics: [...DEFAULT_SELECTED_METRICS],
+  compareBaseline: '',
+  compareScope: 'same', // 'same' | 'cross'
 
-  // Cross-language comparison
-  crossLangGroupsByLang: {}, // langId -> groups[]
+  /** @type {Record<string, Record<string, object[]>>} lang → policy → groups */
+  crossLangGroupsByLangPolicy: {},
+  crossLangGroupsByLang: {},
   xlTestData: '',
-  xlMode: '', // normalized: 'bytes' | 'stream' | other
-  xlSelected: [], // [{ lang, serializer }]
-  xlSelectionMode: 'pareto', // 'pareto' | 'custom'
+  xlMode: '',
+  xlSelected: [],
+  xlSelectionMode: 'pareto',
+  xlBaselineKey: '', // "lang|serializer"
 
-  // Historical data state
   currentRunId: '',
   currentRunConfigs: {},
   currentRunErrors: '',
   currentRunCsv: '',
-  historicalRuns: {} // Maps language -> array of runIds
+  historicalRuns: {},
+  logsAvailable: null, // null unknown, true/false after probe
+  chartLogScale: false,
+  crossLangLoaded: false,
 };
 
-/** Fill the main Language toolbar select from LANGUAGE_CATALOG (single source of truth). */
+function languageLabel(langId) {
+  return LANGUAGE_CATALOG.find((l) => l.id === langId)?.label || langId;
+}
+
 function populateLanguageSelect() {
-  const sel = document.getElementById('lang-select');
-  if (!sel) return;
-  const prev = sel.value || state.currentLanguage;
-  sel.innerHTML = '';
-  for (const lang of LANGUAGE_CATALOG) {
-    const opt = document.createElement('option');
-    opt.value = lang.id;
-    opt.textContent = lang.label;
-    sel.appendChild(opt);
-  }
-  if ([...sel.options].some((o) => o.value === prev)) {
-    sel.value = prev;
-  } else if (sel.options.length) {
-    sel.value = sel.options[0].value;
-    state.currentLanguage = sel.value;
+  const sels = [
+    document.getElementById('lang-select'),
+    document.getElementById('same-lang-select'),
+  ].filter(Boolean);
+  if (!sels.length) return;
+  const prev = state.currentLanguage;
+  sels.forEach((sel) => {
+    sel.innerHTML = '';
+    for (const lang of LANGUAGE_CATALOG) {
+      const opt = document.createElement('option');
+      opt.value = lang.id;
+      opt.textContent = lang.label;
+      sel.appendChild(opt);
+    }
+    if ([...sel.options].some((o) => o.value === prev)) {
+      sel.value = prev;
+    } else if (sel.options.length) {
+      sel.value = sel.options[0].value;
+    }
+  });
+  if (sels[0] && ![...sels[0].options].some((o) => o.value === state.currentLanguage)) {
+    state.currentLanguage = sels[0].value;
   }
 }
 
-// Initialize elements
+/** Keep toolbar + Compare same-language filters in sync. */
+function syncLanguageSelects() {
+  ['lang-select', 'same-lang-select'].forEach((id) => {
+    const el = document.getElementById(id);
+    if (el && [...el.options].some((o) => o.value === state.currentLanguage)) {
+      el.value = state.currentLanguage;
+    }
+  });
+}
+
+function syncFixtureModeSelects() {
+  ['data-select', 'same-data-select'].forEach((id) => {
+    const el = document.getElementById(id);
+    if (el && [...el.options].some((o) => o.value === state.currentTestData)) {
+      el.value = state.currentTestData;
+    }
+  });
+  ['mode-select', 'same-mode-select'].forEach((id) => {
+    const el = document.getElementById(id);
+    if (el && [...el.options].some((o) => o.value === state.currentMode)) {
+      el.value = state.currentMode;
+    }
+  });
+}
+
 document.addEventListener('DOMContentLoaded', async () => {
   populateLanguageSelect();
   applySavedSettings(loadSettings());
+  applyUrlParams();
   setupEventListeners();
   initCharts();
   applyUiFromState();
   await loadHistoryList();
-  await Promise.all([
-    loadLanguageData(state.currentLanguage),
-    loadAllLanguagesForCrossCompare(),
-  ]);
+  await probeLogsAvailability();
+  await loadLanguageData(state.currentLanguage);
+  // Lazy: do not load all langs until cross-lang compare is opened
+  if (state.compareScope === 'cross') {
+    await ensureCrossLangLoaded();
+  }
+  syncUrlFromState();
 });
 
 function loadSettings() {
   try {
     const raw = localStorage.getItem(SETTINGS_KEY);
-    if (!raw) return null;
+    if (!raw) {
+      // migrate v1
+      const v1 = localStorage.getItem('serializer-dashboard-settings-v1');
+      if (v1) return JSON.parse(v1);
+      return null;
+    }
     return JSON.parse(raw);
   } catch (e) {
     console.warn('Could not read saved dashboard settings:', e);
@@ -174,28 +315,33 @@ function saveSettings() {
     currentTestData: state.currentTestData,
     currentMode: state.currentMode,
     displayMetric: state.displayMetric,
+    rosterMetric: state.rosterMetric,
+    rankSort: state.rankSort,
     searchQuery: state.searchQuery,
     sortKey: state.sortKey,
     sortDirection: state.sortDirection,
-    compareA: state.compareA,
-    compareB: state.compareB,
     detailSerializers: state.detailSerializers,
     selectedMetrics: state.selectedMetrics,
+    compareBaseline: state.compareBaseline,
+    compareScope: state.compareScope,
     xlTestData: state.xlTestData,
     xlMode: state.xlMode,
     xlSelected: state.xlSelected,
     xlSelectionMode: state.xlSelectionMode,
+    xlBaselineKey: state.xlBaselineKey,
+    chartLogScale: state.chartLogScale,
+    filterPolicy: state.filterPolicy,
   };
   try {
     localStorage.setItem(SETTINGS_KEY, JSON.stringify(payload));
   } catch (e) {
     console.warn('Could not persist dashboard settings:', e);
   }
+  syncUrlFromState();
 }
 
 function applySavedSettings(saved) {
   if (!saved || typeof saved !== 'object') return;
-
   if (typeof saved.currentLanguage === 'string' && saved.currentLanguage) {
     state.currentLanguage = saved.currentLanguage;
   }
@@ -204,14 +350,18 @@ function applySavedSettings(saved) {
   if (saved.displayMetric === 'ops' || saved.displayMetric === 'time') {
     state.displayMetric = saved.displayMetric;
   }
+  if (saved.rosterMetric === 'ops' || saved.rosterMetric === 'time') {
+    state.rosterMetric = saved.rosterMetric;
+  }
+  if (saved.rankSort === 'speed' || saved.rankSort === 'size') {
+    state.rankSort = saved.rankSort;
+    setRankSort(state.rankSort);
+  }
   if (typeof saved.searchQuery === 'string') state.searchQuery = saved.searchQuery;
   if (typeof saved.sortKey === 'string' && saved.sortKey) state.sortKey = saved.sortKey;
   if (saved.sortDirection === 'asc' || saved.sortDirection === 'desc') {
     state.sortDirection = saved.sortDirection;
   }
-  if (typeof saved.compareA === 'string') state.compareA = saved.compareA;
-  if (typeof saved.compareB === 'string') state.compareB = saved.compareB;
-  // Multi-select (new) with migration from single detailSerializer
   if (Array.isArray(saved.detailSerializers)) {
     state.detailSerializers = saved.detailSerializers.filter((s) => typeof s === 'string');
   } else if (typeof saved.detailSerializer === 'string' && saved.detailSerializer) {
@@ -220,6 +370,14 @@ function applySavedSettings(saved) {
   if (Array.isArray(saved.selectedMetrics) && saved.selectedMetrics.length > 0) {
     state.selectedMetrics = saved.selectedMetrics.filter((k) => typeof k === 'string');
   }
+  if (typeof saved.compareBaseline === 'string') state.compareBaseline = saved.compareBaseline;
+  // migrate old compareA as baseline
+  if (!state.compareBaseline && typeof saved.compareA === 'string') {
+    state.compareBaseline = saved.compareA;
+  }
+  if (saved.compareScope === 'same' || saved.compareScope === 'cross') {
+    state.compareScope = saved.compareScope;
+  }
   if (typeof saved.xlTestData === 'string') state.xlTestData = saved.xlTestData;
   if (typeof saved.xlMode === 'string') state.xlMode = saved.xlMode;
   if (saved.xlSelectionMode === 'pareto' || saved.xlSelectionMode === 'custom') {
@@ -230,556 +388,1774 @@ function applySavedSettings(saved) {
       .filter((x) => x && typeof x.lang === 'string' && typeof x.serializer === 'string')
       .map((x) => ({ lang: x.lang, serializer: x.serializer }));
   }
+  if (typeof saved.xlBaselineKey === 'string') state.xlBaselineKey = saved.xlBaselineKey;
+  if (typeof saved.filterPolicy === 'string' && saved.filterPolicy) {
+    state.filterPolicy = saved.filterPolicy;
+  }
+  if (typeof saved.chartLogScale === 'boolean') {
+    state.chartLogScale = saved.chartLogScale;
+    setChartLogScale(state.chartLogScale);
+  }
+}
+
+function applyUrlParams() {
+  const p = new URLSearchParams(window.location.search);
+  if (p.has('lang')) state.currentLanguage = p.get('lang');
+  if (p.has('data')) state.currentTestData = p.get('data');
+  if (p.has('mode')) state.currentMode = p.get('mode');
+  if (p.get('metric') === 'ops' || p.get('metric') === 'time') state.displayMetric = p.get('metric');
+  if (p.get('scope') === 'cross' || p.get('scope') === 'same') state.compareScope = p.get('scope');
+  if (p.has('baseline')) state.compareBaseline = p.get('baseline');
+  if (p.has('log')) state.chartLogScale = p.get('log') === '1';
+  if (p.get('rank') === 'size' || p.get('rank') === 'speed') {
+    state.rankSort = p.get('rank');
+    setRankSort(state.rankSort);
+  }
+  setChartLogScale(state.chartLogScale);
+}
+
+function syncUrlFromState() {
+  try {
+    const p = new URLSearchParams();
+    p.set('lang', state.currentLanguage);
+    if (state.currentTestData) p.set('data', state.currentTestData);
+    if (state.currentMode) p.set('mode', state.currentMode);
+    p.set('metric', state.displayMetric);
+    if (state.compareScope === 'cross') p.set('scope', 'cross');
+    if (state.compareBaseline) p.set('baseline', state.compareBaseline);
+    if (state.chartLogScale) p.set('log', '1');
+    if (state.rankSort === 'size') p.set('rank', 'size');
+    const qs = p.toString();
+    const url = `${window.location.pathname}${qs ? `?${qs}` : ''}${window.location.hash || ''}`;
+    window.history.replaceState(null, '', url);
+  } catch (_) {
+    /* ignore */
+  }
 }
 
-/** Sync non-data-dependent controls from state (before/after data load). */
 function applyUiFromState() {
   const langSel = document.getElementById('lang-select');
   if (langSel && [...langSel.options].some((o) => o.value === state.currentLanguage)) {
     langSel.value = state.currentLanguage;
   }
 
-  document.getElementById('btn-ops-sec').classList.toggle('active', state.displayMetric === 'ops');
-  document.getElementById('btn-time-ns').classList.toggle('active', state.displayMetric === 'time');
+  document.getElementById('btn-ops-sec')?.classList.toggle('active', state.displayMetric === 'ops');
+  document.getElementById('btn-time-ns')?.classList.toggle('active', state.displayMetric === 'time');
+  document.getElementById('btn-roster-ops')?.classList.toggle('active', state.rosterMetric === 'ops');
+  document.getElementById('btn-roster-latency')?.classList.toggle('active', state.rosterMetric === 'time');
+  document.getElementById('btn-chart-log')?.classList.toggle('active', state.chartLogScale);
+  document.getElementById('btn-rank-sort-speed')?.classList.toggle('active', state.rankSort !== 'size');
+  document.getElementById('btn-rank-sort-size')?.classList.toggle('active', state.rankSort === 'size');
+  setRankSort(state.rankSort);
+  updateRankSortPrimaryLabel();
 
   const search = document.getElementById('table-search');
   if (search) search.value = state.searchQuery || '';
 
-  // Restore sort indicator on multi-serializer table headers
+  updateSortIndicators();
+  applyCompareScopeUi();
+}
+
+/** Rank-sort primary button: Ops/s vs Latency (not generic "Speed"). */
+function updateRankSortPrimaryLabel() {
+  const btn = document.getElementById('btn-rank-sort-speed');
+  if (!btn) return;
+  if (state.displayMetric === 'time') {
+    btn.textContent = 'Latency';
+    btn.title = 'Sort by latency (lowest first)';
+  } else {
+    btn.textContent = 'Ops/s';
+    btn.title = 'Sort by ops/s (highest first)';
+  }
+}
+
+
+function updateSortIndicators() {
   document.querySelectorAll('#analytics-table th').forEach((th) => {
-    th.className = '';
+    th.classList.remove('sort-asc', 'sort-desc');
   });
   const sortHeaderMap = {
     serializer: 'th-serializer',
-    avg_ops_per_sec: 'th-ops',
-    avg_time_total_ns: 'th-total-ns',
-    avg_time_ser_ns: 'th-ser-ns',
-    avg_time_deser_ns: 'th-deser-ns',
+    ops_median: 'th-ops-median',
+    ops_std: 'th-ops-std',
+    ops_p95: 'th-ops-p95',
+    ops_p99: 'th-ops-p99',
+    total_median_ns: 'th-lat-median',
+    total_std_ns: 'th-lat-std',
+    total_p95_ns: 'th-lat-p95',
+    total_p99_ns: 'th-lat-p99',
     median_size_bytes: 'th-size',
   };
   const sortTh = document.getElementById(sortHeaderMap[state.sortKey]);
   if (sortTh) {
-    sortTh.className = state.sortDirection === 'asc' ? 'sort-asc' : 'sort-desc';
+    sortTh.classList.add(state.sortDirection === 'asc' ? 'sort-asc' : 'sort-desc');
+  }
+}
+
+function applyCompareScopeUi() {
+  const same = state.compareScope === 'same';
+  document.getElementById('btn-compare-same')?.classList.toggle('active', same);
+  document.getElementById('btn-compare-xl')?.classList.toggle('active', !same);
+  const sameFilters = document.getElementById('compare-same-filters');
+  const xlFilters = document.getElementById('compare-xl-filters');
+  const samePanel = document.getElementById('compare-same-panel');
+  const xlPanel = document.getElementById('xl-add-panel');
+  const sameChips = document.getElementById('same-selection-chips');
+  const xlChips = document.getElementById('xl-selection-chips');
+  const disclaimer = document.getElementById('compare-xl-disclaimer');
+  const badge = document.getElementById('compare-scope-badge');
+  const serAll = document.getElementById('detail-ser-select-all');
+  const seedPareto = document.getElementById('xl-reset-pareto');
+
+  if (sameFilters) sameFilters.hidden = !same;
+  if (xlFilters) xlFilters.hidden = same;
+  if (samePanel) samePanel.hidden = !same;
+  if (xlPanel) xlPanel.hidden = same;
+  if (sameChips) sameChips.hidden = !same;
+  if (xlChips) xlChips.hidden = same;
+  if (disclaimer) disclaimer.hidden = same;
+  if (serAll) serAll.hidden = !same;
+  if (seedPareto) seedPareto.hidden = same;
+  if (badge) {
+    badge.hidden = true; // status line + Same/Cross tabs already convey mode
+  }
+  updateCompareStatusLine();
+}
+
+function updateCompareStatusLine() {
+  const el = document.getElementById('compare-status-line');
+  const countEl = document.getElementById('compare-selected-count');
+  const metricsEl = document.getElementById('metrics-selected-count');
+  let n = 0;
+  if (state.compareScope === 'same') {
+    n = state.detailSerializers.filter((s) => state.serializerNames.includes(s)).length;
+  } else {
+    n = state.xlSelected.length;
   }
+  const m = state.selectedMetrics.filter((k) =>
+    state.availableMetrics.length ? state.availableMetrics.includes(k) : true
+  ).length;
+  if (el) {
+    const serLabel = n === 1 ? 'serializer' : 'serializers';
+    const metLabel = m === 1 ? 'metric' : 'metrics';
+    el.textContent = `${n} ${serLabel} · ${m} ${metLabel}`;
+  }
+  if (countEl) countEl.textContent = String(n);
+  if (metricsEl) metricsEl.textContent = String(m);
 }
 
 function setupEventListeners() {
-  // Selectors
-  document.getElementById('lang-select').addEventListener('change', async (e) => {
+  document.getElementById('filter-policy-select')?.addEventListener('change', (e) => {
+    setFilterPolicy(e.target.value);
+  });
+
+  // Mobile nav
+  const navToggle = document.getElementById('nav-toggle');
+  const mainNav = document.getElementById('main-nav');
+  navToggle?.addEventListener('click', () => {
+    const open = mainNav?.classList.toggle('open');
+    navToggle.setAttribute('aria-expanded', open ? 'true' : 'false');
+  });
+
+  const onLanguageChange = async (e) => {
     state.currentLanguage = e.target.value;
+    syncLanguageSelects();
     saveSettings();
     await loadLanguageData(state.currentLanguage);
-  });
+  };
+  document.getElementById('lang-select')?.addEventListener('change', onLanguageChange);
+  document.getElementById('same-lang-select')?.addEventListener('change', onLanguageChange);
 
-  document.getElementById('data-select').addEventListener('change', (e) => {
+  const onDataChange = (e) => {
     state.currentTestData = e.target.value;
+    syncFixtureModeSelects();
     saveSettings();
     filterAndRefresh();
-  });
+  };
+  document.getElementById('data-select')?.addEventListener('change', onDataChange);
+  document.getElementById('same-data-select')?.addEventListener('change', onDataChange);
 
-  document.getElementById('mode-select').addEventListener('change', (e) => {
+  const onModeChange = (e) => {
     state.currentMode = e.target.value;
+    syncFixtureModeSelects();
     saveSettings();
     filterAndRefresh();
-  });
+  };
+  document.getElementById('mode-select')?.addEventListener('change', onModeChange);
+  document.getElementById('same-mode-select')?.addEventListener('change', onModeChange);
+
+  document.getElementById('btn-ops-sec')?.addEventListener('click', () => setViewMetric('ops'));
+  document.getElementById('btn-time-ns')?.addEventListener('click', () => setViewMetric('time'));
 
-  // Toggle View Tabs
-  document.getElementById('btn-ops-sec').addEventListener('click', () => {
-    setViewMetric('ops');
+  document.getElementById('btn-roster-ops')?.addEventListener('click', () => setRosterMetric('ops'));
+  document.getElementById('btn-roster-latency')?.addEventListener('click', () => setRosterMetric('time'));
+
+  document.getElementById('btn-chart-log')?.addEventListener('click', () => {
+    state.chartLogScale = !state.chartLogScale;
+    setChartLogScale(state.chartLogScale);
+    document.getElementById('btn-chart-log')?.classList.toggle('active', state.chartLogScale);
+    saveSettings();
+    updateCharts(state.filteredGroups, state.paretoSerializerNames, state.displayMetric);
   });
 
-  document.getElementById('btn-time-ns').addEventListener('click', () => {
-    setViewMetric('time');
+  const setRankingSort = (sort) => {
+    state.rankSort = sort === 'size' ? 'size' : 'speed';
+    setRankSort(state.rankSort);
+    document.getElementById('btn-rank-sort-speed')?.classList.toggle('active', state.rankSort === 'speed');
+    document.getElementById('btn-rank-sort-size')?.classList.toggle('active', state.rankSort === 'size');
+    updateRankSortPrimaryLabel();
+    saveSettings();
+    updateCharts(state.filteredGroups, state.paretoSerializerNames, state.displayMetric);
+  };
+  document.getElementById('btn-rank-sort-speed')?.addEventListener('click', () => setRankingSort('speed'));
+  document.getElementById('btn-rank-sort-size')?.addEventListener('click', () => setRankingSort('size'));
+
+  document.getElementById('btn-export-scatter')?.addEventListener('click', () => {
+    const url = exportScatterPng();
+    if (url) downloadDataUrl(url, `scatter-${state.currentLanguage}.png`);
+  });
+  document.getElementById('btn-export-bar')?.addEventListener('click', () => {
+    const url = exportBarPng();
+    if (url) downloadDataUrl(url, `ranking-${state.currentLanguage}.png`);
   });
 
-  // Search Input
-  document.getElementById('table-search').addEventListener('input', (e) => {
+  document.getElementById('table-search')?.addEventListener('input', (e) => {
     state.searchQuery = e.target.value.toLowerCase().trim();
     saveSettings();
     renderTable();
   });
 
-  // Table Sorting
   const headers = [
     { id: 'th-serializer', key: 'serializer' },
-    { id: 'th-ops', key: 'avg_ops_per_sec' },
-    { id: 'th-total-ns', key: 'avg_time_total_ns' },
-    { id: 'th-ser-ns', key: 'avg_time_ser_ns' },
-    { id: 'th-deser-ns', key: 'avg_time_deser_ns' },
-    { id: 'th-size', key: 'median_size_bytes' }
+    { id: 'th-ops-median', key: 'ops_median' },
+    { id: 'th-ops-std', key: 'ops_std' },
+    { id: 'th-ops-p95', key: 'ops_p95' },
+    { id: 'th-ops-p99', key: 'ops_p99' },
+    { id: 'th-lat-median', key: 'total_median_ns' },
+    { id: 'th-lat-std', key: 'total_std_ns' },
+    { id: 'th-lat-p95', key: 'total_p95_ns' },
+    { id: 'th-lat-p99', key: 'total_p99_ns' },
+    { id: 'th-size', key: 'median_size_bytes' },
   ];
-
-  headers.forEach(h => {
+  headers.forEach((h) => {
     const el = document.getElementById(h.id);
-    if (el) {
-      el.addEventListener('click', () => handleTableSort(h.key, el));
-    }
+    if (el) el.addEventListener('click', () => handleTableSort(h.key));
   });
 
-  // Comparison Selects
-  document.getElementById('compare-a-select').addEventListener('change', (e) => {
-    state.compareA = e.target.value;
+  const onBaselineChange = (e) => {
+    state.compareBaseline = e.target.value;
+    // Keep roster + compare pickers in sync
+    const otherIds = ['compare-baseline-select', 'roster-baseline-select'];
+    otherIds.forEach((id) => {
+      const el = document.getElementById(id);
+      if (el && el !== e.target && [...el.options].some((o) => o.value === state.compareBaseline)) {
+        el.value = state.compareBaseline;
+      }
+    });
+    // Ensure baseline is in compare selection
+    if (
+      state.compareScope === 'same' &&
+      state.compareBaseline &&
+      !state.detailSerializers.includes(state.compareBaseline)
+    ) {
+      state.detailSerializers = [state.compareBaseline, ...state.detailSerializers].slice(
+        0,
+        MAX_COMPARE_COLUMNS
+      );
+    }
+    saveSettings();
+    renderSameSelectionChips();
+    populateSameSerAddSelect();
+    renderTable();
+    renderCompareMatrix();
+  };
+  document.getElementById('compare-baseline-select')?.addEventListener('change', onBaselineChange);
+  document.getElementById('roster-baseline-select')?.addEventListener('change', onBaselineChange);
+
+  document.getElementById('btn-compare-same')?.addEventListener('click', () => {
+    state.compareScope = 'same';
+    applyCompareScopeUi();
+    renderSameSelectionChips();
+    populateSameSerAddSelect();
     saveSettings();
-    updateComparison();
+    renderCompareMatrix();
   });
 
-  document.getElementById('compare-b-select').addEventListener('change', (e) => {
-    state.compareB = e.target.value;
+  document.getElementById('btn-compare-xl')?.addEventListener('click', async () => {
+    state.compareScope = 'cross';
+    applyCompareScopeUi();
     saveSettings();
-    updateComparison();
+    await ensureCrossLangLoaded();
+    renderCrossLangSelection();
+    renderCompareMatrix();
   });
 
-  // Multi-serializer metrics explorer
-  document.getElementById('detail-ser-select-all').addEventListener('click', () => {
-    state.detailSerializers = [...state.serializerNames];
+  document.getElementById('detail-ser-select-all')?.addEventListener('click', () => {
+    // Same-language only: add all (capped)
+    state.detailSerializers = state.serializerNames.slice(0, MAX_COMPARE_COLUMNS);
+    if (
+      state.compareBaseline &&
+      !state.detailSerializers.includes(state.compareBaseline) &&
+      state.serializerNames.includes(state.compareBaseline)
+    ) {
+      state.detailSerializers = [
+        state.compareBaseline,
+        ...state.detailSerializers.filter((s) => s !== state.compareBaseline),
+      ].slice(0, MAX_COMPARE_COLUMNS);
+    }
     saveSettings();
-    renderDetailSerializerChecklist();
-    renderSerializerMetricsTable();
+    renderSameSelectionChips();
+    populateSameSerAddSelect();
+    renderCompareMatrix();
+    updateCompareStatusLine();
   });
 
-  document.getElementById('detail-ser-select-none').addEventListener('click', () => {
-    state.detailSerializers = [];
+  document.getElementById('detail-ser-select-none')?.addEventListener('click', () => {
+    if (state.compareScope === 'same') {
+      state.detailSerializers = state.compareBaseline ? [state.compareBaseline] : [];
+      renderSameSelectionChips();
+      populateSameSerAddSelect();
+    } else {
+      state.xlSelected = [];
+      state.xlSelectionMode = 'custom';
+      renderCrossLangSelection();
+      updateXlBaselineSelect();
+    }
     saveSettings();
-    renderDetailSerializerChecklist();
-    renderSerializerMetricsTable();
+    renderCompareMatrix();
+    updateCompareStatusLine();
+  });
+
+  document.getElementById('same-ser-search')?.addEventListener('input', () => {
+    populateSameSerAddSelect();
+  });
+
+  document.getElementById('same-ser-add-btn')?.addEventListener('click', () => {
+    addSameLanguageSerializer(document.getElementById('same-ser-add-select')?.value);
   });
 
-  document.getElementById('metrics-select-all').addEventListener('click', () => {
+  document.getElementById('same-ser-add-select')?.addEventListener('keydown', (e) => {
+    if (e.key === 'Enter') {
+      e.preventDefault();
+      addSameLanguageSerializer(e.target.value);
+    }
+  });
+
+  document.getElementById('metrics-select-all')?.addEventListener('click', () => {
     state.selectedMetrics = [...state.availableMetrics];
+    setMetricsPresetActive('custom');
+    openMetricsPanel(true);
     saveSettings();
     renderMetricsChecklist();
-    renderSerializerMetricsTable();
+    renderCompareMatrix();
+    updateCompareStatusLine();
   });
 
-  document.getElementById('metrics-select-none').addEventListener('click', () => {
+  document.getElementById('metrics-select-none')?.addEventListener('click', () => {
     state.selectedMetrics = [];
+    setMetricsPresetActive('custom');
+    openMetricsPanel(true);
     saveSettings();
     renderMetricsChecklist();
-    renderSerializerMetricsTable();
+    renderCompareMatrix();
+    updateCompareStatusLine();
   });
 
-  document.getElementById('metrics-select-default').addEventListener('click', () => {
-    state.selectedMetrics = DEFAULT_SELECTED_METRICS.filter((k) =>
-      state.availableMetrics.includes(k)
-    );
-    if (state.selectedMetrics.length === 0) {
-      state.selectedMetrics = state.availableMetrics.slice(0, 12);
-    }
-    saveSettings();
-    renderMetricsChecklist();
-    renderSerializerMetricsTable();
+  document.getElementById('metrics-select-default')?.addEventListener('click', () => {
+    applyMetricPreset('defaults');
+  });
+  document.getElementById('metrics-preset-latency')?.addEventListener('click', () => {
+    applyMetricPreset('latency');
+  });
+  document.getElementById('metrics-preset-size')?.addEventListener('click', () => {
+    applyMetricPreset('size');
+  });
+  document.getElementById('metrics-edit-toggle')?.addEventListener('click', () => {
+    const body = document.getElementById('metrics-panel-body');
+    const open = body && body.hidden;
+    openMetricsPanel(!!open);
+    setMetricsPresetActive('custom');
   });
 
-  // Cross-language comparison
-  document.getElementById('xl-data-select').addEventListener('change', (e) => {
+  // Cross-lang filters
+  document.getElementById('xl-data-select')?.addEventListener('change', (e) => {
     state.xlTestData = e.target.value;
-    if (state.xlSelectionMode === 'pareto') {
-      applyCrossLangParetoSelection();
-    } else {
-      pruneCrossLangSelection();
-    }
+    if (state.xlSelectionMode === 'pareto') applyCrossLangParetoSelection();
+    else pruneCrossLangSelection();
     refreshCrossLangAddSerializerOptions();
     renderCrossLangSelection();
-    renderCrossLangTable();
+    updateXlBaselineSelect();
+    renderCompareMatrix();
     saveSettings();
+    updateCompareStatusLine();
   });
 
-  document.getElementById('xl-mode-select').addEventListener('change', (e) => {
+  document.getElementById('xl-mode-select')?.addEventListener('change', (e) => {
     state.xlMode = e.target.value;
-    if (state.xlSelectionMode === 'pareto') {
-      applyCrossLangParetoSelection();
-    } else {
-      pruneCrossLangSelection();
-    }
+    if (state.xlSelectionMode === 'pareto') applyCrossLangParetoSelection();
+    else pruneCrossLangSelection();
     refreshCrossLangAddSerializerOptions();
     renderCrossLangSelection();
-    renderCrossLangTable();
+    updateXlBaselineSelect();
+    renderCompareMatrix();
     saveSettings();
+    updateCompareStatusLine();
   });
 
-  document.getElementById('xl-reset-pareto').addEventListener('click', () => {
+  document.getElementById('xl-reset-pareto')?.addEventListener('click', () => {
     state.xlSelectionMode = 'pareto';
     applyCrossLangParetoSelection();
+    // Cap columns for readability
+    if (state.xlSelected.length > MAX_COMPARE_COLUMNS) {
+      state.xlSelected = state.xlSelected.slice(0, MAX_COMPARE_COLUMNS);
+    }
     renderCrossLangSelection();
-    renderCrossLangTable();
-    updateCrossLangBadge();
+    updateXlBaselineSelect();
+    refreshCrossLangAddSerializerOptions();
+    renderCompareMatrix();
     saveSettings();
+    updateCompareStatusLine();
   });
 
-  document.getElementById('xl-add-lang').addEventListener('change', () => {
+  document.getElementById('xl-add-lang')?.addEventListener('change', () => {
     refreshCrossLangAddSerializerOptions();
   });
 
-  document.getElementById('xl-add-btn').addEventListener('click', () => {
+  document.getElementById('xl-add-btn')?.addEventListener('click', () => {
     const lang = document.getElementById('xl-add-lang').value;
     const serializer = document.getElementById('xl-add-serializer').value;
     if (!lang || !serializer) return;
-    const exists = state.xlSelected.some(
-      (x) => x.lang === lang && x.serializer === serializer
-    );
-    if (exists) {
+    if (state.xlSelected.some((x) => x.lang === lang && x.serializer === serializer)) {
       showNotification('Already selected for comparison.', 'info');
       return;
     }
-    // Only add if a matching group exists under current filters
+    if (state.xlSelected.length >= MAX_COMPARE_COLUMNS) {
+      showNotification(`At most ${MAX_COMPARE_COLUMNS} serializers in Compare.`, 'info');
+      return;
+    }
     const group = findCrossLangGroup(lang, serializer);
     if (!group) {
-      showNotification('No data for that serializer under the current Test Data / Mode.', 'error');
+      showNotification('No data for that serializer under the current data type / mode.', 'error');
       return;
     }
     state.xlSelectionMode = 'custom';
     state.xlSelected = [...state.xlSelected, { lang, serializer }];
     renderCrossLangSelection();
-    renderCrossLangTable();
-    updateCrossLangBadge();
+    updateXlBaselineSelect();
+    refreshCrossLangAddSerializerOptions();
+    renderCompareMatrix();
+    saveSettings();
+    updateCompareStatusLine();
+  });
+
+  document.getElementById('compare-xl-baseline-select')?.addEventListener('change', (e) => {
+    state.xlBaselineKey = e.target.value;
     saveSettings();
+    renderCrossLangSelection();
+    renderCompareMatrix();
   });
 
-  // Navigation Links for Smooth Scrolling
-  const navLinks = document.querySelectorAll('.nav-links a');
-  navLinks.forEach(link => {
+  document.getElementById('btn-copy-roster-md')?.addEventListener('click', () => copyRosterMarkdown());
+  document.getElementById('btn-copy-compare-md')?.addEventListener('click', () => copyCompareMarkdown());
+
+  // Nav smooth scroll
+  document.querySelectorAll('.nav-links a').forEach((link) => {
     link.addEventListener('click', (e) => {
       const href = link.getAttribute('href');
       if (href && href.startsWith('#')) {
         e.preventDefault();
-        // Remove active class
-        document.querySelectorAll('.nav-links li').forEach(li => li.classList.remove('active'));
+        document.querySelectorAll('.nav-links li').forEach((li) => li.classList.remove('active'));
         link.parentElement.classList.add('active');
-        
-        const targetId = href.substring(1);
-        const targetElement = document.getElementById(targetId);
-        if (targetElement) {
-          targetElement.scrollIntoView({ behavior: 'smooth', block: 'start' });
-        }
+        document.getElementById(href.slice(1))?.scrollIntoView({ behavior: 'smooth', block: 'start' });
+        // close mobile nav
+        document.getElementById('main-nav')?.classList.remove('open');
+        document.getElementById('nav-toggle')?.setAttribute('aria-expanded', 'false');
       }
     });
   });
 
-  // Drag and Drop Upload Setup
+  // Upload
   const dropZone = document.getElementById('drop-zone');
   const fileInput = document.getElementById('file-input');
-
-  dropZone.addEventListener('click', () => fileInput.click());
-  fileInput.addEventListener('change', (e) => handleFileUpload(e.target.files[0]));
-
-  ['dragenter', 'dragover'].forEach(eventName => {
-    dropZone.addEventListener(eventName, (e) => {
+  dropZone?.addEventListener('click', () => fileInput?.click());
+  fileInput?.addEventListener('change', (e) => handleFileUpload(e.target.files[0]));
+  ['dragenter', 'dragover'].forEach((ev) => {
+    dropZone?.addEventListener(ev, (e) => {
       e.preventDefault();
       dropZone.classList.add('dragover');
-    }, false);
+    });
   });
-
-  ['dragleave', 'drop'].forEach(eventName => {
-    dropZone.addEventListener(eventName, (e) => {
+  ['dragleave', 'drop'].forEach((ev) => {
+    dropZone?.addEventListener(ev, (e) => {
       e.preventDefault();
       dropZone.classList.remove('dragover');
-    }, false);
-  });
-
-  dropZone.addEventListener('drop', (e) => {
-    const dt = e.dataTransfer;
-    const files = dt.files;
-    handleFileUpload(files[0]);
+    });
   });
-
-  // History Actions Setup
-  document.getElementById('history-run-select').addEventListener('change', (e) => {
-    const runId = e.target.value;
-    const disabled = !runId;
-    document.getElementById('download-csv-btn').disabled = disabled;
-    document.getElementById('download-config-btn').disabled = disabled;
-    document.getElementById('download-error-btn').disabled = disabled;
-    document.getElementById('load-history-btn').disabled = disabled;
+  dropZone?.addEventListener('drop', (e) => handleFileUpload(e.dataTransfer.files[0]));
+
+  // History
+  document.getElementById('history-run-select')?.addEventListener('change', (e) => {
+    const disabled = !e.target.value || state.logsAvailable === false;
+    ['download-csv-btn', 'download-config-btn', 'download-error-btn', 'load-history-btn'].forEach(
+      (id) => {
+        const b = document.getElementById(id);
+        if (b) b.disabled = disabled;
+      }
+    );
   });
 
-  document.getElementById('download-csv-btn').addEventListener('click', () => {
+  document.getElementById('download-csv-btn')?.addEventListener('click', () => {
     const runId = document.getElementById('history-run-select').value;
     if (runId) {
-      triggerDownload(`/logs/${state.currentLanguage}/${runId}.csv`, `${state.currentLanguage}_${runId}.csv`);
+      triggerDownload(
+        logsUrl(`${state.currentLanguage}/${runId}.csv`),
+        `${state.currentLanguage}_${runId}.csv`
+      );
     }
   });
 
-  document.getElementById('download-config-btn').addEventListener('click', () => {
+  document.getElementById('download-config-btn')?.addEventListener('click', () => {
     const runId = document.getElementById('history-run-select').value;
     if (runId) {
-      const url = `/logs/${state.currentLanguage}/${runId}.configs.json`;
-      const fallbackUrl = `/logs/${state.currentLanguage}/${runId}.environment.json`;
-      downloadFileWithFallback(url, fallbackUrl, `${state.currentLanguage}_${runId}.configs.json`);
+      downloadFileWithFallback(
+        logsUrl(`${state.currentLanguage}/${runId}.configs.json`),
+        logsUrl(`${state.currentLanguage}/${runId}.environment.json`),
+        `${state.currentLanguage}_${runId}.configs.json`
+      );
     }
   });
 
-  document.getElementById('download-error-btn').addEventListener('click', () => {
+  document.getElementById('download-error-btn')?.addEventListener('click', () => {
     const runId = document.getElementById('history-run-select').value;
     if (runId) {
-      const url = `/logs/${state.currentLanguage}/${runId}.errors.csv`;
-      downloadFileWithFallback(url, null, `${state.currentLanguage}_${runId}.errors.csv`);
+      downloadFileWithFallback(
+        logsUrl(`${state.currentLanguage}/${runId}.errors.csv`),
+        null,
+        `${state.currentLanguage}_${runId}.errors.csv`
+      );
     }
   });
 
-  document.getElementById('load-history-btn').addEventListener('click', async () => {
+  document.getElementById('load-history-btn')?.addEventListener('click', async () => {
     const runId = document.getElementById('history-run-select').value;
-    if (runId) {
-      await loadHistoricalRunIntoDashboard(runId);
-    }
+    if (runId) await loadHistoricalRunIntoDashboard(runId);
   });
 }
 
-// Load available historical runs index
+function logsUrl(path) {
+  // Relative to dashboard base (Vite base: './')
+  return `logs/${path}`;
+}
+
+async function probeLogsAvailability() {
+  try {
+    // Try a lightweight probe against available_runs path sibling
+    const runs = state.historicalRuns[state.currentLanguage];
+    if (!runs || !runs.length) {
+      state.logsAvailable = false;
+    } else {
+      const probe = await fetch(logsUrl(`${state.currentLanguage}/${runs[0]}.csv`), {
+        method: 'HEAD',
+      });
+      state.logsAvailable = probe.ok;
+    }
+  } catch {
+    state.logsAvailable = false;
+  }
+  const localNote = document.getElementById('history-local-note');
+  const pagesNote = document.getElementById('history-pages-note');
+  if (localNote) localNote.hidden = state.logsAvailable === false;
+  if (pagesNote) pagesNote.hidden = state.logsAvailable !== false;
+  if (state.logsAvailable === false) {
+    ['download-csv-btn', 'download-config-btn', 'download-error-btn', 'load-history-btn'].forEach(
+      (id) => {
+        const b = document.getElementById(id);
+        if (b) b.disabled = true;
+      }
+    );
+  }
+}
+
 async function loadHistoryList() {
   try {
     const response = await fetch('data/available_runs.json');
-    if (!response.ok) throw new Error("Could not fetch available runs index");
+    if (!response.ok) throw new Error('Could not fetch available runs index');
     state.historicalRuns = await response.json();
   } catch (e) {
-    console.error("History runs not indexable (or offline):", e);
+    console.error('History runs not indexable (or offline):', e);
   }
 }
 
-// Populate the history dropdown for the current language
 function updateHistoryUIForLanguage() {
   const select = document.getElementById('history-run-select');
-  select.innerHTML = '<option value="">-- Select Run ID --</option>';
-  
+  if (!select) return;
+  select.innerHTML = '<option value="">— Select run ID —</option>';
   const runs = state.historicalRuns[state.currentLanguage] || [];
-  runs.forEach(runId => {
+  runs.forEach((runId) => {
     const opt = document.createElement('option');
     opt.value = runId;
-    opt.textContent = runId + (runId === state.currentRunId ? ' (Currently Active)' : '');
+    opt.textContent = runId + (runId === state.currentRunId ? ' (currently active)' : '');
     select.appendChild(opt);
   });
-
-  // Reset buttons
   select.value = '';
-  document.getElementById('download-csv-btn').disabled = true;
-  document.getElementById('download-config-btn').disabled = true;
-  document.getElementById('download-error-btn').disabled = true;
-  document.getElementById('load-history-btn').disabled = true;
+  ['download-csv-btn', 'download-config-btn', 'download-error-btn', 'load-history-btn'].forEach(
+    (id) => {
+      const b = document.getElementById(id);
+      if (b) b.disabled = true;
+    }
+  );
+}
+
+/**
+ * Fetch JSON or gzip-JSON from a URL.
+ * @param {string} url
+ * @returns {Promise<object|null>}
+ */
+async function fetchJsonMaybeGzip(url) {
+  const res = await fetch(url);
+  if (!res.ok) return null;
+  try {
+    return await res.clone().json();
+  } catch {
+    const ds = new DecompressionStream('gzip');
+    const text = await new Response(res.body.pipeThrough(ds)).text();
+    return JSON.parse(text);
+  }
+}
+
+/**
+ * Prefer standalone multi-policy stats (gzip first); fall back to embedded stats.
+ * @param {string} lang
+ * @param {object|null} gzStats
+ */
+async function loadStatsObjectForLanguage(lang, gzStats) {
+  const urls = [
+    `data/stats_${lang}_latest.json.gz`,
+    `data/stats_${lang}_latest.json`,
+  ];
+  for (const statsUrl of urls) {
+    try {
+      const obj = await fetchJsonMaybeGzip(statsUrl);
+      if (obj && (obj.groups_by_policy || obj.groups)) return obj;
+    } catch (e) {
+      console.warn(`Could not load ${statsUrl}:`, e);
+    }
+  }
+  return gzStats || { groups: [] };
 }
 
-// Load packed compressed run data (.json.gz)
 async function loadLanguageData(lang) {
   const url = `data/${lang}_latest.json.gz`;
   try {
     const response = await fetch(url);
     if (!response.ok) throw new Error(`Could not load stats for ${lang}`);
-    
+
     let payload;
-    // Check if the response is already decompressed (e.g. Content-Encoding handled by browser)
     try {
-      const clonedResponse = response.clone();
-      payload = await clonedResponse.json();
-    } catch (e) {
-      // Fallback: manually decompress using DecompressionStream
-      try {
-        const ds = new DecompressionStream('gzip');
-        const decompressedStream = response.body.pipeThrough(ds);
-        const text = await new Response(decompressedStream).text();
-        payload = JSON.parse(text);
-      } catch (decompError) {
-        throw new Error(`Failed to parse or decompress payload: ${decompError.message}`);
-      }
+      payload = await response.clone().json();
+    } catch {
+      const ds = new DecompressionStream('gzip');
+      const text = await new Response(response.body.pipeThrough(ds)).text();
+      payload = JSON.parse(text);
     }
 
     state.currentRunId = payload.run_id;
-    state.currentRunConfigs = payload.configs;
-    state.currentRunErrors = payload.errors;
-    state.currentRunCsv = payload.csv_data;
+    state.currentRunConfigs = payload.configs || {};
+    state.currentRunErrors = payload.errors || '';
+    state.currentRunCsv = payload.csv_data || '';
 
-    processStatsData(payload.stats);
+    const statsObj = await loadStatsObjectForLanguage(lang, payload.stats);
+    processStatsData(statsObj);
+    updateRunMeta();
     updateHistoryUIForLanguage();
   } catch (error) {
     console.error(error);
+    // Last resort: stats-only file without gz package
+    try {
+      const statsObj = await loadStatsObjectForLanguage(lang, null);
+      if (statsObj.groups?.length || statsObj.groups_by_policy) {
+        processStatsData(statsObj);
+        updateRunMeta();
+        updateHistoryUIForLanguage();
+        return;
+      }
+    } catch (_) {
+      /* ignore */
+    }
     showNotification(`Error loading ${lang} stats. Please run sync script first.`, 'error');
+    setKpiEmpty('No data');
   }
 }
 
-// Load historical raw run dynamically into dashboard
-async function loadHistoricalRunIntoDashboard(runId) {
-  const csvUrl = `/logs/${state.currentLanguage}/${runId}.csv`;
-  const configUrl = `/logs/${state.currentLanguage}/${runId}.configs.json`;
-  const fallbackConfigUrl = `/logs/${state.currentLanguage}/${runId}.environment.json`;
+function formatHostMemory(mem) {
+  const bytes = mem?.total_bytes ?? mem?.total ?? null;
+  if (typeof bytes !== 'number' || !Number.isFinite(bytes) || bytes <= 0) return null;
+  const gib = bytes / (1024 ** 3);
+  if (gib >= 10) return `${Math.round(gib)} GiB RAM`;
+  return `${formatSig(gib, 3)} GiB RAM`;
+}
+
+function updateRunMeta() {
+  const el = document.getElementById('run-meta');
+  const text = document.getElementById('run-meta-text');
+  if (!el || !text) return;
+  const cfg = state.currentRunConfigs || {};
+  const env = cfg.environment || cfg; // packed env sometimes flat
+  const cpu = env.cpu || {};
+  const mem = env.memory || {};
+  const runtimes = env.runtimes || {};
+  const dataset = cfg.dataset || {};
+  const parts = [];
+  // Run id is the provenance key for this payload (not git commit — can disagree with other runs).
+  if (state.currentRunId) parts.push(`run ${state.currentRunId}`);
+  if (cpu.model) {
+    const cores = cpu.logical_cores || cpu.cpu_count;
+    parts.push(cores ? `${cpu.model} (${cores} threads)` : cpu.model);
+  }
+  const ram = formatHostMemory(mem);
+  if (ram) parts.push(ram);
+  const rtKey =
+    state.currentLanguage === 'csharp'
+      ? 'dotnet'
+      : state.currentLanguage === 'javascript'
+        ? 'node'
+        : state.currentLanguage === 'cpp'
+          ? 'g++'
+          : state.currentLanguage === 'c'
+            ? 'gcc'
+            : state.currentLanguage;
+  const rtLabel =
+    {
+      csharp: '.NET',
+      javascript: 'Node',
+      python: 'Python',
+      rust: 'rustc',
+      go: 'Go',
+      java: 'Java',
+      c: 'gcc',
+      cpp: 'g++',
+      swift: 'Swift',
+    }[state.currentLanguage] || 'runtime';
+  if (runtimes[rtKey]) {
+    // Strip redundant product name if the version string already starts with it
+    let ver = String(runtimes[rtKey]).split('\n')[0].trim();
+    ver = ver.replace(/^rustc\s+/i, '').replace(/^go\s+version\s+/i, 'go ');
+    parts.push(`${rtLabel} ${ver}`);
+  }
+  if (dataset.seed != null) parts.push(`seed ${dataset.seed}`);
+  if (parts.length) {
+    text.textContent = parts.join(' · ');
+    el.hidden = false;
+  } else {
+    el.hidden = true;
+  }
+}
 
-  showNotification(`Loading historical run ${runId}...`, 'info');
+async function loadHistoricalRunIntoDashboard(runId) {
+  const csvUrl = logsUrl(`${state.currentLanguage}/${runId}.csv`);
+  const configUrl = logsUrl(`${state.currentLanguage}/${runId}.configs.json`);
+  const fallbackConfigUrl = logsUrl(`${state.currentLanguage}/${runId}.environment.json`);
 
+  showNotification(`Loading historical run ${runId}…`, 'info');
   try {
-    // 1. Fetch CSV
     const csvRes = await fetch(csvUrl);
     if (!csvRes.ok) throw new Error(`Could not fetch raw CSV for run ${runId}`);
     const csvText = await csvRes.text();
 
-    // 2. Fetch Config
     let configs = {};
     try {
       let confRes = await fetch(configUrl);
       if (!confRes.ok) confRes = await fetch(fallbackConfigUrl);
       if (confRes.ok) configs = await confRes.json();
     } catch (e) {
-      console.warn("Failed to load configs sidecar for history run:", e);
+      console.warn('Failed to load configs sidecar for history run:', e);
     }
 
-    // 3. Parse CSV and aggregate stats dynamically
     const records = parseCSV(csvText);
     const groups = aggregateCSVRecords(records);
-
-    if (groups.length === 0) {
-      throw new Error("No valid serializer records found in parsed CSV.");
-    }
+    if (groups.length === 0) throw new Error('No valid serializer records found in parsed CSV.');
 
     state.currentRunId = runId;
     state.currentRunConfigs = configs;
     state.currentRunCsv = csvText;
-    state.currentRunErrors = ''; // Cleared for historical local
-
-    // Swap datasets
+    state.currentRunErrors = '';
     processStatsData({ groups });
-    
-    // Update active indicators
-    document.getElementById('history-run-select').value = runId;
-    document.getElementById('load-history-btn').disabled = false;
-
-    showNotification(`Successfully loaded run ${runId} into Dashboard!`, 'success');
+    updateRunMeta();
+    showNotification(`Successfully loaded run ${runId}`, 'success');
   } catch (error) {
-    console.error("Error loading historical run:", error);
+    console.error(error);
     showNotification(`Failed to load historical run: ${error.message}`, 'error');
   }
 }
 
-function processStatsData(statsObj) {
-  // Normalize groups to display fixture keys (type@n=N when batch axis present)
-  state.allGroups = (statsObj.groups || []).map((g) => ({
-    ...g,
-    test_data: fixtureKey(g),
-  }));
-
-  // Suite fixtures only in the data-type dropdown
-  const testDataOptions = [
-    ...new Set(
-      state.allGroups
-        .map((g) => g.test_data)
-        .filter((k) => k && SUITE_TYPE_IDS.includes(baseTypeId(k)))
-    ),
-  ].sort();
-  const modeOptions = [...new Set(state.allGroups.map(g => g.mode))];
+const GROUP_IDENTITY_KEYS = new Set([
+  'serializer',
+  'test_data',
+  'type_config_hash',
+  'data_type_instance_count',
+  'mode',
+  'language',
+  'serializer_version',
+  'StreamMode',
+  'variants',
+]);
 
-  // Populate Dropdowns
-  populateSelect('data-select', testDataOptions);
-  populateSelect('mode-select', modeOptions);
+/**
+ * Expand schema 2.2 identity+variants groups into flat per-policy rows.
+ * Merges catalog label/description into each filter block (export omits them).
+ * @param {object[]} slimGroups
+ * @param {Record<string, object>} catalog
+ * @returns {Record<string, object[]>}
+ */
+function expandVariantGroups(slimGroups, catalog) {
+  /** @type {Record<string, object[]>} */
+  const byPolicy = {};
+  for (const g of slimGroups) {
+    const variants = g.variants;
+    if (!variants || typeof variants !== 'object') continue;
+    const identity = {};
+    for (const [k, v] of Object.entries(g)) {
+      if (!GROUP_IDENTITY_KEYS.has(k) || k === 'variants') continue;
+      identity[k] = v;
+    }
+    // Always copy known identity fields even if null
+    for (const k of [
+      'serializer',
+      'test_data',
+      'type_config_hash',
+      'data_type_instance_count',
+      'mode',
+      'language',
+      'serializer_version',
+    ]) {
+      if (k in g) identity[k] = g[k];
+    }
+    if (g.StreamMode != null) identity.StreamMode = g.StreamMode;
+
+    for (const [pid, metrics] of Object.entries(variants)) {
+      if (!metrics || typeof metrics !== 'object') continue;
+      const cat = catalog[pid] || FILTER_POLICY_FALLBACK[pid] || {};
+      const filter = { ...(metrics.filter || {}) };
+      if (filter.label == null && cat.label) filter.label = cat.label;
+      if (filter.description == null && cat.description) filter.description = cat.description;
+      if (filter.policy == null) filter.policy = pid;
+      const row = {
+        ...identity,
+        ...metrics,
+        filter,
+        test_data: fixtureKey({ ...identity, ...metrics }),
+      };
+      if (!byPolicy[pid]) byPolicy[pid] = [];
+      byPolicy[pid].push(row);
+    }
+  }
+  return byPolicy;
+}
 
-  // Prefer saved filters when still valid
-  if (!testDataOptions.includes(state.currentTestData)) {
-    state.currentTestData = pickPreferredFixture(testDataOptions);
+/**
+ * Normalize a stats export (schema 2.0 / 2.1 / 2.2) into groupsByPolicy.
+ * @param {object} statsObj
+ * @returns {{ groupsByPolicy: Record<string, object[]>, defaultPolicy: string, catalog: object }}
+ */
+function normalizeStatsPayload(statsObj) {
+  const raw = statsObj || {};
+  const catalog = {
+    ...FILTER_POLICY_FALLBACK,
+    ...(raw.filter_policies && typeof raw.filter_policies === 'object'
+      ? raw.filter_policies
+      : {}),
+  };
+  const defaultPolicy =
+    typeof raw.default_filter_policy === 'string' && raw.default_filter_policy
+      ? raw.default_filter_policy
+      : DEFAULT_FILTER_POLICY;
+
+  const mapGroups = (list) =>
+    (Array.isArray(list) ? list : []).map((g) => ({
+      ...g,
+      test_data: fixtureKey(g),
+    }));
+
+  /** @type {Record<string, object[]>} */
+  let groupsByPolicy = {};
+
+  // Schema 2.2: identity once + variants
+  const rawGroups = Array.isArray(raw.groups) ? raw.groups : [];
+  const isSlimVariants =
+    rawGroups.length > 0 &&
+    rawGroups.some((g) => g && typeof g === 'object' && g.variants && typeof g.variants === 'object');
+
+  if (isSlimVariants) {
+    groupsByPolicy = expandVariantGroups(rawGroups, catalog);
+  } else if (raw.groups_by_policy && typeof raw.groups_by_policy === 'object') {
+    // Schema 2.1
+    for (const [pid, list] of Object.entries(raw.groups_by_policy)) {
+      groupsByPolicy[pid] = mapGroups(list);
+    }
   }
-  if (!modeOptions.includes(state.currentMode)) {
-    state.currentMode = modeOptions[0] || '';
+
+  // Schema 2.0 / fallback: flat groups = single policy
+  if (!Object.keys(groupsByPolicy).length && rawGroups.length) {
+    groupsByPolicy[defaultPolicy] = mapGroups(rawGroups);
+  } else if (rawGroups.length && !isSlimVariants && !groupsByPolicy[defaultPolicy]?.length) {
+    groupsByPolicy[defaultPolicy] = mapGroups(rawGroups);
   }
 
-  document.getElementById('data-select').value = state.currentTestData;
-  document.getElementById('mode-select').value = state.currentMode;
+  return { groupsByPolicy, defaultPolicy, catalog };
+}
 
-  state.availableMetrics = discoverMetricKeys(state.allGroups);
-  // Keep only selected metrics that still exist; if none left, fall back to defaults
-  state.selectedMetrics = state.selectedMetrics.filter((k) =>
-    state.availableMetrics.includes(k)
-  );
-  if (state.selectedMetrics.length === 0) {
-    state.selectedMetrics = DEFAULT_SELECTED_METRICS.filter((k) =>
-      state.availableMetrics.includes(k)
-    );
-    if (state.selectedMetrics.length === 0) {
-      state.selectedMetrics = state.availableMetrics.slice(0, 12);
-    }
+function processStatsData(statsObj) {
+  const { groupsByPolicy, defaultPolicy, catalog } = normalizeStatsPayload(statsObj);
+  state.groupsByPolicy = groupsByPolicy;
+  state.defaultFilterPolicy = defaultPolicy;
+  state.filterPolicies = catalog;
+
+  // Keep selection if still available; else fall back to export default
+  const available = Object.keys(groupsByPolicy);
+  if (!available.includes(state.filterPolicy)) {
+    state.filterPolicy = available.includes(defaultPolicy)
+      ? defaultPolicy
+      : available[0] || DEFAULT_FILTER_POLICY;
   }
 
-  renderMetricsChecklist();
+  applyFilterPolicyToAllGroups({ refreshSelectors: true });
+  populateFilterPolicySelect();
+  syncLanguageSelects();
+  syncFixtureModeSelects();
+  discoverMetricKeys(state.allGroups);
   filterAndRefresh();
-  saveSettings();
 }
 
-function discoverMetricKeys(groups) {
-  const keys = new Set();
-  for (const g of groups) {
-    if (!g || typeof g !== 'object') continue;
-    for (const k of Object.keys(g)) {
-      if (!GROUP_META_KEYS.has(k)) keys.add(k);
+/** Bind state.allGroups from the active filter policy. */
+function applyFilterPolicyToAllGroups({ refreshSelectors = false } = {}) {
+  const pid = state.filterPolicy;
+  const groups =
+    state.groupsByPolicy[pid] ||
+    state.groupsByPolicy[state.defaultFilterPolicy] ||
+    state.groupsByPolicy[DEFAULT_FILTER_POLICY] ||
+    [];
+  state.allGroups = groups;
+
+  if (refreshSelectors) {
+    const discovered = discoverFixtureOptions(state.allGroups);
+    const testDataOptions = discovered.all;
+    const modeOptions = [...new Set(state.allGroups.map((g) => g.mode))];
+
+    populateFixtureSelect(testDataOptions);
+    populateFixtureSelect(testDataOptions, {
+      selectId: 'same-data-select',
+      previous: state.currentTestData,
+    });
+    populateSelect('mode-select', modeOptions);
+    populateSelect('same-mode-select', modeOptions);
+
+    if (!testDataOptions.includes(state.currentTestData)) {
+      state.currentTestData =
+        pickPreferredFixture(discovered.natural) || testDataOptions[0] || '';
+    }
+    if (!modeOptions.includes(state.currentMode)) {
+      state.currentMode = modeOptions[0] || '';
     }
   }
-  return [...keys].sort((a, b) => a.localeCompare(b));
 }
 
-function populateSelect(id, options) {
-  const select = document.getElementById(id);
-  select.innerHTML = '';
-  options.forEach(opt => {
-    const el = document.createElement('option');
-    el.value = opt;
-    el.textContent = opt;
-    select.appendChild(el);
-  });
-}
+function populateFilterPolicySelect() {
+  const sel = document.getElementById('filter-policy-select');
+  if (!sel) return;
+  const available = FILTER_POLICY_ORDER.filter((id) => state.groupsByPolicy[id]?.length);
+  const extras = Object.keys(state.groupsByPolicy).filter((id) => !available.includes(id));
+  const ids = available.length ? [...available, ...extras] : Object.keys(state.groupsByPolicy);
 
-// Filter dataset based on selected test_data & mode
-function filterAndRefresh() {
-  state.filteredGroups = state.allGroups.filter(g =>
-    g.test_data === state.currentTestData && g.mode === state.currentMode
-  );
+  sel.innerHTML = '';
+  if (!ids.length) {
+    const opt = document.createElement('option');
+    opt.value = DEFAULT_FILTER_POLICY;
+    opt.textContent = FILTER_POLICY_FALLBACK[DEFAULT_FILTER_POLICY]?.label || DEFAULT_FILTER_POLICY;
+    sel.appendChild(opt);
+    sel.disabled = true;
+    return;
+  }
+  sel.disabled = ids.length <= 1;
+  for (const id of ids) {
+    const meta = state.filterPolicies[id] || FILTER_POLICY_FALLBACK[id] || { label: id };
+    const opt = document.createElement('option');
+    opt.value = id;
+    opt.textContent = meta.label || id;
+    sel.appendChild(opt);
+  }
+  if (ids.includes(state.filterPolicy)) sel.value = state.filterPolicy;
+  else {
+    state.filterPolicy = ids[0];
+    sel.value = ids[0];
+  }
+}
 
-  // Re-calculate Pareto frontier dynamically
-  calculateParetoFrontier();
+function setFilterPolicy(policyId) {
+  if (!policyId) return;
+  if (!(policyId in state.groupsByPolicy)) {
+    showNotification(`Sample policy “${policyId}” not in this export.`, 'error');
+    return;
+  }
+  state.filterPolicy = policyId;
+  applyFilterPolicyToAllGroups({ refreshSelectors: false });
+  discoverMetricKeys(state.allGroups);
+  if (state.crossLangLoaded) {
+    rebuildCrossLangForPolicy();
+  }
+  filterAndRefresh();
+  if (state.compareScope === 'cross') {
+    renderCrossLangSelection();
+    renderCompareMatrix();
+  }
+}
 
-  // Populate comparison pickers
-  state.serializerNames = state.filteredGroups.map(g => g.serializer).sort();
-  populateCompareSelectors();
-  populateDetailSerializerSelect();
+function updateFilterPolicyMeta() {
+  const el = document.getElementById('filter-policy-meta');
+  const text = document.getElementById('filter-policy-meta-text');
+  if (!el || !text) return;
+
+  const pid = state.filterPolicy;
+  const catalog = state.filterPolicies[pid] || FILTER_POLICY_FALLBACK[pid] || {};
+  const sample = state.filteredGroups[0] || state.allGroups[0];
+  const f = sample?.filter || {};
+
+  const removed = state.filteredGroups.length
+    ? state.filteredGroups.reduce((a, g) => a + (Number(g.outliers_removed) || 0), 0)
+    : state.allGroups.reduce((a, g) => a + (Number(g.outliers_removed) || 0), 0);
+  const clipped = state.filteredGroups.length
+    ? state.filteredGroups.reduce((a, g) => a + (Number(g.values_clipped) || 0), 0)
+    : state.allGroups.reduce((a, g) => a + (Number(g.values_clipped) || 0), 0);
+  const kept = state.filteredGroups.length
+    ? state.filteredGroups.reduce((a, g) => a + (Number(g.runs) || 0), 0)
+    : null;
+
+  const criteriaBits = [];
+  const method = f.method || catalog.outlier_method;
+  if (method) criteriaBits.push(`method=${method}`);
+  if (f.iqr_k != null || catalog.iqr_k != null) {
+    criteriaBits.push(`k=${f.iqr_k ?? catalog.iqr_k}`);
+  }
+  if (f.winsorize_percentiles || catalog.winsorize_percentiles) {
+    const w = f.winsorize_percentiles || catalog.winsorize_percentiles;
+    criteriaBits.push(`clip=${Array.isArray(w) ? w.join('–') : w}%`);
+  }
+  if (f.paired === true || catalog.paired === true) criteriaBits.push('paired ser/deser/total');
+  if (f.exclude_warmup !== false && catalog.exclude_warmup !== false) {
+    criteriaBits.push('warmup excluded');
+  }
+  if (f.min_samples_for_outlier_filter != null || catalog.min_samples_for_outlier_filter != null) {
+    criteriaBits.push(
+      `min_n=${f.min_samples_for_outlier_filter ?? catalog.min_samples_for_outlier_filter}`
+    );
+  }
+  if (f.fence_total_low_ns != null && f.fence_total_high_ns != null && sample) {
+    criteriaBits.push(
+      `e.g. total fences [${formatTimeCompact(f.fence_total_low_ns)}, ${formatTimeCompact(f.fence_total_high_ns)}] on ${sample.serializer}`
+    );
+  }
 
-  // Update summary widgets
-  updateKPIs();
+  const statsBits = [];
+  if (kept != null) statsBits.push(`${formatIntGrouped(kept)} trials kept (current data type)`);
+  if (removed > 0) statsBits.push(`${formatIntGrouped(removed)} reps removed (sum over rows)`);
+  if (clipped > 0) statsBits.push(`${formatIntGrouped(clipped)} reps clipped (winsorize, sum)`);
 
-  // Render visualizations
-  updateCharts(state.filteredGroups, state.paretoSerializerNames, state.displayMetric);
+  const desc = catalog.description || f.description || '';
+  text.innerHTML =
+    `<strong>Samples: ${catalog.label || pid}</strong>` +
+    (desc ? ` — ${desc}` : '') +
+    (criteriaBits.length
+      ? `<br><span class="fp-criteria">Criteria: ${criteriaBits.join(' · ')}</span>`
+      : '') +
+    (statsBits.length
+      ? `<br><span class="fp-criteria">This view: ${statsBits.join(' · ')}</span>`
+      : '');
+  el.hidden = false;
+}
 
-  // Render Table
-  renderTable();
+function discoverMetricKeys(groups) {
+  const keys = new Set();
+  for (const g of groups) {
+    for (const k of Object.keys(g)) {
+      if (GROUP_META_KEYS.has(k) || k === 'data_type_instance_count') continue;
+      if (typeof g[k] === 'object' && g[k] !== null) continue; // skip filter blocks etc.
+      keys.add(k);
+    }
+  }
+  state.availableMetrics = [...keys].sort();
+  // Keep selected intersection; fill defaults if empty
+  state.selectedMetrics = state.selectedMetrics.filter((k) => state.availableMetrics.includes(k));
+  if (!state.selectedMetrics.length) {
+    state.selectedMetrics = DEFAULT_SELECTED_METRICS.filter((k) =>
+      state.availableMetrics.includes(k)
+    );
+  }
+}
+
+function populateSelect(id, options) {
+  const sel = document.getElementById(id);
+  if (!sel) return;
+  const prev = sel.value;
+  sel.innerHTML = '';
+  options.forEach((o) => {
+    const opt = document.createElement('option');
+    opt.value = o;
+    opt.textContent = o;
+    sel.appendChild(opt);
+  });
+  if (options.includes(prev)) sel.value = prev;
+}
+
+/**
+ * Test Data select with grouped synthetic data-type labels.
+ * @param {string[]} options
+ * @param {{ selectId?: string, previous?: string }} [cfg]
+ */
+function populateFixtureSelect(options, cfg = {}) {
+  const selectId = cfg.selectId || 'data-select';
+  const sel = document.getElementById(selectId);
+  if (!sel) return;
+  const prev = cfg.previous != null ? cfg.previous : sel.value || state.currentTestData;
+  sel.innerHTML = '';
+
+  const natural = options.filter((o) => parseFixtureSelection(o).kind === 'natural');
+  const batchCompound = options.filter((o) => parseFixtureSelection(o).kind === 'batch_compound');
+  const allTypes = options.filter((o) => parseFixtureSelection(o).kind === 'all_n');
+  const allAll = options.filter((o) => parseFixtureSelection(o).kind === 'all_all');
+
+  const addOpt = (o) => {
+    const opt = document.createElement('option');
+    opt.value = o;
+    opt.textContent = fixtureOptionLabel(o);
+    sel.appendChild(opt);
+  };
+  const addSep = (label) => {
+    const sep = document.createElement('option');
+    sep.disabled = true;
+    sep.textContent = label;
+    sel.appendChild(sep);
+  };
+
+  natural.forEach(addOpt);
+  if (batchCompound.length) {
+    addSep('── compounded batch ──');
+    batchCompound.forEach(addOpt);
+  }
+  if (allTypes.length) {
+    addSep('── compounded data types ──');
+    allTypes.forEach(addOpt);
+  }
+  if (allAll.length) {
+    addSep('── compounded all ──');
+    allAll.forEach(addOpt);
+  }
+
+  if ([...sel.options].some((o) => o.value === prev)) {
+    sel.value = prev;
+  } else if (sel.options.length) {
+    const first = [...sel.options].find((o) => !o.disabled && o.value);
+    if (first) sel.value = first.value;
+  }
+}
+
+/**
+ * Docs Summary aggregation (reports._scientific_summary_md intent):
+ * - Prefer bytes/string mode when present for a serializer (else keep all modes).
+ * - Restrict to suite data-type base ids (message, document, …).
+ * - One value per field: arithmetic mean across remaining groups;
+ *   `runs` is summed; non-numeric: first non-empty (e.g. serializer_version).
+ * - `total_median_ns` falls back to `avg_time_total_ns` when missing.
+ */
+
+/** Instance count from group (column or @n= suffix). */
+function instanceCount(g) {
+  let n = g?.data_type_instance_count;
+  if (n != null && n !== '') {
+    const num = Number(n);
+    if (Number.isFinite(num) && num > 0) return num;
+  }
+  const m = String(g?.test_data ?? '').match(/@n=(\d+)/i);
+  return m ? Number(m[1]) : null;
+}
 
-  // Update Side-by-side comparison
-  updateComparison();
+/**
+ * Data-type selection kinds:
+ * - natural: message@n=1
+ * - batch_compound: message@n=1+100 (same type, two batch sizes)
+ * - all_n: all@1 / all@100 (all suite types at fixed n)
+ * - all_all: all@all (all suite types × all n)
+ */
+function parseFixtureSelection(key) {
+  const s = String(key || '').trim();
+  if (!s) return { kind: 'natural', key: s };
+  if (s === 'all@all') return { kind: 'all_all', key: s };
+  let m = s.match(/^all@n=(\d+)$/i) || s.match(/^all@(\d+)$/i);
+  if (m) return { kind: 'all_n', key: s, n: Number(m[1]) };
+  m = s.match(/^(.+)@n=(\d+)\+(\d+)$/i);
+  if (m) {
+    return {
+      kind: 'batch_compound',
+      key: s,
+      base: m[1],
+      nA: Number(m[2]),
+      nB: Number(m[3]),
+    };
+  }
+  return { kind: 'natural', key: s };
+}
 
-  // Single-serializer metrics table
-  renderSerializerMetricsTable();
+/** @deprecated use parseFixtureSelection; kept for call sites that only need batch compound */
+function parseCompoundFixture(key) {
+  const p = parseFixtureSelection(key);
+  if (p.kind === 'batch_compound') return { base: p.base, nA: p.nA, nB: p.nB };
+  return null;
+}
+
+function compoundFixtureKey(base, nA, nB) {
+  const a = Math.min(nA, nB);
+  const b = Math.max(nA, nB);
+  return `${base}@n=${a}+${b}`;
+}
 
+function isSyntheticFixture(key) {
+  const k = parseFixtureSelection(key).kind;
+  return k === 'batch_compound' || k === 'all_n' || k === 'all_all';
+}
+
+function isCompoundFixture(key) {
+  return isSyntheticFixture(key);
+}
+
+/**
+ * Average numeric fields across a list of groups (same serializer).
+ * runs: sum; total_median_ns falls back to avg_time_total_ns.
+ */
+function averageGroupsForSerializer(serializer, entries, meta) {
+  const row = {
+    serializer,
+    test_data: meta.test_data,
+    mode: meta.mode,
+    language: entries[0]?.language || state.currentLanguage,
+    compounded: !!meta.compounded,
+    compound_parts: meta.compound_parts || null,
+  };
+  let version = '';
+  for (const e of entries) {
+    if (e.serializer_version) {
+      version = String(e.serializer_version).trim();
+      break;
+    }
+  }
+  if (version) row.serializer_version = version;
+
+  const numericKeys = new Set();
+  for (const e of entries) {
+    for (const [k, v] of Object.entries(e)) {
+      if (GROUP_META_KEYS.has(k) || k === 'data_type_instance_count') continue;
+      if (typeof v === 'number' && Number.isFinite(v)) numericKeys.add(k);
+    }
+  }
+  for (const key of numericKeys) {
+    const vals = [];
+    for (const e of entries) {
+      let v = e[key];
+      if ((v === null || v === undefined) && key === 'total_median_ns') {
+        v = e.avg_time_total_ns;
+      }
+      if (typeof v === 'number' && Number.isFinite(v)) vals.push(v);
+    }
+    if (!vals.length) continue;
+    row[key] =
+      key === 'runs' ||
+      key === 'runs_raw' ||
+      key === 'outliers_removed' ||
+      key === 'values_clipped' ||
+      key === 'warmup_skipped'
+        ? vals.reduce((a, b) => a + b, 0)
+        : vals.reduce((a, b) => a + b, 0) / vals.length;
+  }
+  if (row.avg_time_total_ns == null && row.total_median_ns != null) {
+    row.avg_time_total_ns = row.total_median_ns;
+  }
+  if (row.avg_ops_per_sec == null && row.avg_time_total_ns > 0) {
+    row.avg_ops_per_sec = 1e9 / row.avg_time_total_ns;
+  }
+  return row;
+}
+
+/**
+ * Build compounded rows: for each serializer, mean of n=A and n=B groups
+ * for the same base type + mode.
+ */
+function buildCompoundedFixtureGroups(allGroups, base, nA, nB, mode) {
+  const want = new Set([nA, nB]);
+  const matched = (allGroups || []).filter((g) => {
+    if (baseTypeId(g.test_data) !== base) return false;
+    if (String(g.mode) !== String(mode)) return false;
+    const n = instanceCount(g);
+    return n != null && want.has(n);
+  });
+
+  const bySer = new Map();
+  for (const g of matched) {
+    if (!bySer.has(g.serializer)) bySer.set(g.serializer, []);
+    bySer.get(g.serializer).push(g);
+  }
+
+  const test_data = compoundFixtureKey(base, nA, nB);
+  const out = [];
+  for (const [serializer, entries] of bySer) {
+    // Prefer serializers that have both batch sizes
+    const ns = new Set(entries.map(instanceCount).filter((x) => x != null));
+    if (!ns.has(nA) || !ns.has(nB)) continue;
+    // One group per n (if duplicates, average those first)
+    const perN = new Map();
+    for (const e of entries) {
+      const n = instanceCount(e);
+      if (!perN.has(n)) perN.set(n, []);
+      perN.get(n).push(e);
+    }
+    const parts = [];
+    for (const n of [nA, nB]) {
+      const list = perN.get(n) || [];
+      if (list.length === 1) parts.push(list[0]);
+      else if (list.length > 1) {
+        parts.push(
+          averageGroupsForSerializer(serializer, list, {
+            test_data: `${base}@n=${n}`,
+            mode,
+            compounded: false,
+          })
+        );
+      }
+    }
+    if (parts.length < 2) continue;
+    out.push(
+      averageGroupsForSerializer(serializer, parts, {
+        test_data,
+        mode,
+        compounded: true,
+        compound_parts: `${base}@n=${nA} + ${base}@n=${nB}`,
+      })
+    );
+  }
+  return out.sort((a, b) => a.serializer.localeCompare(b.serializer));
+}
+
+/**
+ * all@1 / all@100: mean across all suite data types at a fixed instance count.
+ * One contribution per base type (if multiple rows, pre-averaged).
+ */
+function buildAllTypesAtNGroups(allGroups, n, mode) {
+  const matched = (allGroups || []).filter((g) => {
+    if (!SUITE_TYPE_IDS.includes(baseTypeId(g.test_data))) return false;
+    if (String(g.mode) !== String(mode)) return false;
+    return instanceCount(g) === n;
+  });
+
+  const bySer = new Map();
+  for (const g of matched) {
+    if (!bySer.has(g.serializer)) bySer.set(g.serializer, []);
+    bySer.get(g.serializer).push(g);
+  }
+
+  const test_data = `all@${n}`;
+  const out = [];
+  for (const [serializer, entries] of bySer) {
+    // One value per base type, then mean across types
+    const byBase = new Map();
+    for (const e of entries) {
+      const base = baseTypeId(e.test_data);
+      if (!byBase.has(base)) byBase.set(base, []);
+      byBase.get(base).push(e);
+    }
+    const parts = [];
+    const bases = [];
+    for (const base of SUITE_TYPE_IDS) {
+      const list = byBase.get(base);
+      if (!list || !list.length) continue;
+      bases.push(`${base}@n=${n}`);
+      if (list.length === 1) parts.push(list[0]);
+      else {
+        parts.push(
+          averageGroupsForSerializer(serializer, list, {
+            test_data: `${base}@n=${n}`,
+            mode,
+            compounded: false,
+          })
+        );
+      }
+    }
+    if (parts.length < 1) continue;
+    out.push(
+      averageGroupsForSerializer(serializer, parts, {
+        test_data,
+        mode,
+        compounded: true,
+        compound_parts: bases.join(' + '),
+      })
+    );
+  }
+  return out.sort((a, b) => a.serializer.localeCompare(b.serializer));
+}
+
+/**
+ * all@all: mean across all suite types and all batch sizes (current mode).
+ * Collapse to one row per (base, n) then average those cells.
+ */
+function buildAllAllGroups(allGroups, mode) {
+  const matched = (allGroups || []).filter((g) => {
+    if (!SUITE_TYPE_IDS.includes(baseTypeId(g.test_data))) return false;
+    return String(g.mode) === String(mode);
+  });
+
+  const bySer = new Map();
+  for (const g of matched) {
+    if (!bySer.has(g.serializer)) bySer.set(g.serializer, []);
+    bySer.get(g.serializer).push(g);
+  }
+
+  const out = [];
+  for (const [serializer, entries] of bySer) {
+    const byCell = new Map(); // base@n -> groups
+    for (const e of entries) {
+      const n = instanceCount(e);
+      const base = baseTypeId(e.test_data);
+      if (n == null) continue;
+      const cell = `${base}@n=${n}`;
+      if (!byCell.has(cell)) byCell.set(cell, []);
+      byCell.get(cell).push(e);
+    }
+    const parts = [];
+    const cells = [...byCell.keys()].sort();
+    for (const cell of cells) {
+      const list = byCell.get(cell);
+      if (list.length === 1) parts.push(list[0]);
+      else {
+        parts.push(
+          averageGroupsForSerializer(serializer, list, {
+            test_data: cell,
+            mode,
+            compounded: false,
+          })
+        );
+      }
+    }
+    if (parts.length < 1) continue;
+    out.push(
+      averageGroupsForSerializer(serializer, parts, {
+        test_data: 'all@all',
+        mode,
+        compounded: true,
+        compound_parts: cells.join(' + '),
+      })
+    );
+  }
+  return out.sort((a, b) => a.serializer.localeCompare(b.serializer));
+}
+
+/** Natural + synthetic data-type keys for the Test Data dropdown. */
+function discoverFixtureOptions(allGroups) {
+  const natural = [
+    ...new Set(
+      (allGroups || [])
+        .map((g) => g.test_data)
+        .filter((k) => k && SUITE_TYPE_IDS.includes(baseTypeId(k)))
+    ),
+  ].sort();
+
+  const byBase = new Map();
+  const nsGlobal = new Set();
+  for (const g of allGroups || []) {
+    const base = baseTypeId(g.test_data);
+    if (!SUITE_TYPE_IDS.includes(base)) continue;
+    const n = instanceCount(g);
+    if (n == null) continue;
+    if (!byBase.has(base)) byBase.set(base, new Set());
+    byBase.get(base).add(n);
+    nsGlobal.add(n);
+  }
+
+  // Per-type batch compounds: message@n=1+100, …
+  const batchCompound = [];
+  for (const [base, ns] of byBase) {
+    if (ns.has(1) && ns.has(100)) {
+      batchCompound.push(compoundFixtureKey(base, 1, 100));
+    }
+  }
+  batchCompound.sort();
+
+  // Cross-type at fixed n
+  const allTypes = [];
+  if (nsGlobal.has(1)) allTypes.push('all@1');
+  if (nsGlobal.has(100)) allTypes.push('all@100');
+
+  // Everything
+  const allAll = natural.length ? ['all@all'] : [];
+
+  return {
+    natural,
+    batchCompound,
+    allTypes,
+    allAll,
+    all: [...natural, ...batchCompound, ...allTypes, ...allAll],
+  };
+}
+
+function fixtureOptionLabel(key) {
+  const p = parseFixtureSelection(key);
+  if (p.kind === 'batch_compound') {
+    return `${p.base}@n=${p.nA}+${p.nB} (compounded batch)`;
+  }
+  if (p.kind === 'all_n') {
+    return `all@${p.n} (all data types, n=${p.n})`;
+  }
+  if (p.kind === 'all_all') {
+    return 'all@all (all types × all n)';
+  }
+  return key;
+}
+
+function resolveFixtureGroups() {
+  const sel = parseFixtureSelection(state.currentTestData);
+  const mode = state.currentMode;
+  if (sel.kind === 'batch_compound') {
+    return buildCompoundedFixtureGroups(
+      state.allGroups,
+      sel.base,
+      sel.nA,
+      sel.nB,
+      mode
+    );
+  }
+  if (sel.kind === 'all_n') {
+    return buildAllTypesAtNGroups(state.allGroups, sel.n, mode);
+  }
+  if (sel.kind === 'all_all') {
+    return buildAllAllGroups(state.allGroups, mode);
+  }
+  return state.allGroups.filter(
+    (g) => g.test_data === state.currentTestData && g.mode === mode
+  );
+}
+
+function filterAndRefresh() {
+  state.filteredGroups = resolveFixtureGroups();
+
+  state.serializerNames = [
+    ...new Set(state.filteredGroups.map((g) => g.serializer)),
+  ].sort((a, b) => a.localeCompare(b));
+
+  calculateParetoFrontier();
+
+  // Baseline default
+  if (!state.compareBaseline || !state.serializerNames.includes(state.compareBaseline)) {
+    state.compareBaseline =
+      state.paretoSerializerNames[0] || state.serializerNames[0] || '';
+  }
+
+  // Detail serializers default: baseline + a few others (capped)
+  state.detailSerializers = state.detailSerializers.filter((s) =>
+    state.serializerNames.includes(s)
+  );
+  if (!state.detailSerializers.length) {
+    const seed = state.paretoSerializerNames.length
+      ? state.paretoSerializerNames
+      : state.serializerNames;
+    state.detailSerializers = seed.slice(0, Math.min(6, seed.length));
+  }
+  if (state.compareBaseline && !state.detailSerializers.includes(state.compareBaseline)) {
+    state.detailSerializers = [state.compareBaseline, ...state.detailSerializers].slice(
+      0,
+      MAX_COMPARE_COLUMNS
+    );
+  }
+
+  updateKPIs();
+  updateFilterPolicyMeta();
+  populateBaselineSelect();
+  populateSameSerAddSelect();
+  renderSameSelectionChips();
+  renderMetricsChecklist();
+  renderTable();
+  renderCompareMatrix();
+  updateCharts(state.filteredGroups, state.paretoSerializerNames, state.displayMetric);
+  updateSortIndicators();
+  updateCompareStatusLine();
   saveSettings();
 }
 
 function setViewMetric(metric) {
   state.displayMetric = metric;
-
-  // Update Active Button Style
-  document.getElementById('btn-ops-sec').classList.toggle('active', metric === 'ops');
-  document.getElementById('btn-time-ns').classList.toggle('active', metric === 'time');
-
-  // Redraw charts & table
+  document.getElementById('btn-ops-sec')?.classList.toggle('active', metric === 'ops');
+  document.getElementById('btn-time-ns')?.classList.toggle('active', metric === 'time');
+  updateRankSortPrimaryLabel();
+  saveSettings();
   updateCharts(state.filteredGroups, state.paretoSerializerNames, state.displayMetric);
+}
+
+function setRosterMetric(metric) {
+  state.rosterMetric = metric === 'time' ? 'time' : 'ops';
+  document.getElementById('btn-roster-ops')?.classList.toggle('active', state.rosterMetric === 'ops');
+  document.getElementById('btn-roster-latency')?.classList.toggle('active', state.rosterMetric === 'time');
+  // Reset sort to primary column of the active view
+  const opsKeys = new Set(['ops_median', 'ops_std', 'ops_p95', 'ops_p99']);
+  const latKeys = new Set(['total_median_ns', 'total_std_ns', 'total_p95_ns', 'total_p99_ns']);
+  if (state.rosterMetric === 'ops' && latKeys.has(state.sortKey)) {
+    state.sortKey = 'ops_median';
+    state.sortDirection = 'desc';
+  } else if (state.rosterMetric === 'time' && opsKeys.has(state.sortKey)) {
+    state.sortKey = 'total_median_ns';
+    state.sortDirection = 'asc';
+  }
   saveSettings();
+  renderTable();
 }
 
-// Pareto Frontier Calculation (minimize latency + size)
-function isParetoDominated(g, groups) {
-  const gTime = g.avg_time_total_ns;
-  const gSize = g.median_size_bytes;
-  if (gTime == null || gSize == null) return true;
+/**
+ * Ops stats derived from trial latencies when direct ops percentiles are absent.
+ * (ops ≈ 1e9 / total_ns; percentile of ops inverts latency percentiles.)
+ */
+function invNsToOps(ns) {
+  if (typeof ns !== 'number' || !Number.isFinite(ns) || ns <= 0) return null;
+  return 1e9 / ns;
+}
+
+/** Attach ops_median / ops_std / ops_p95 / ops_p99 for roster display & sort. */
+function withOpsDerivedStats(g) {
+  if (!g) return g;
+  const medianNs = g.total_median_ns ?? g.total_p50_ns ?? g.avg_time_total_ns;
+  const meanNs = g.total_mean_ns ?? g.avg_time_total_ns;
+  const stdNs = g.total_std_ns;
+  // High throughput percentiles ↔ low latency percentiles
+  const p95Ops = invNsToOps(g.total_p5_ns);
+  const p99Ops = invNsToOps(g.total_min_ns ?? g.total_p5_ns);
+  let opsStd = null;
+  if (
+    typeof meanNs === 'number' &&
+    meanNs > 0 &&
+    typeof stdNs === 'number' &&
+    Number.isFinite(stdNs)
+  ) {
+    // Delta method: sd(1e9/T) ≈ 1e9 * sd(T) / E[T]^2
+    opsStd = (1e9 * stdNs) / (meanNs * meanNs);
+  }
+  return {
+    ...g,
+    ops_median: invNsToOps(medianNs) ?? g.avg_ops_per_sec ?? null,
+    ops_std: opsStd,
+    ops_p95: p95Ops ?? g.max_ops_per_sec ?? null,
+    ops_p99: p99Ops ?? g.max_ops_per_sec ?? null,
+  };
+}
+
+/** Roster columns for Detailed Analytics (local Ops/s | Latency switch). */
+function rosterMetricKeys() {
+  if (state.rosterMetric === 'time') {
+    return [
+      { key: 'total_median_ns', higherIsBetter: false, label: 'Median' },
+      { key: 'total_std_ns', higherIsBetter: false, label: 'Std' },
+      { key: 'total_p95_ns', higherIsBetter: false, label: 'P95' },
+      { key: 'total_p99_ns', higherIsBetter: false, label: 'P99' },
+      { key: 'median_size_bytes', higherIsBetter: false, label: 'Median size' },
+    ];
+  }
+  return [
+    { key: 'ops_median', higherIsBetter: true, label: 'Median' },
+    { key: 'ops_std', higherIsBetter: false, label: 'Std' },
+    { key: 'ops_p95', higherIsBetter: true, label: 'P95' },
+    { key: 'ops_p99', higherIsBetter: true, label: 'P99' },
+    { key: 'median_size_bytes', higherIsBetter: false, label: 'Median size' },
+  ];
+}
+
+function formatRosterCell(key, value, scales) {
+  if (value === null || value === undefined) return '—';
+  if (key.startsWith('ops_') || key === 'avg_ops_per_sec') {
+    return formatOpsCell(value, scales.ops);
+  }
+  return formatMetricCell(key, value, scales);
+}
 
-  for (const other of groups) {
-    if (other === g) continue;
-    const otherTime = other.avg_time_total_ns;
-    const otherSize = other.median_size_bytes;
-    if (otherTime == null || otherSize == null) continue;
+/**
+ * Detailed Analytics cell policy:
+ * - Median (ops/latency) & size → absolute + ×base (vs baseline same column)
+ * - Std / P95 / P99 → absolute + ×med (vs that row’s own median)
+ */
+function formatRosterRelativeCell(row, key, higherIsBetter, scales, baselineGroup, isBaseline) {
+  const v = row[key];
+  const ownMedian =
+    key.startsWith('ops_')
+      ? row.ops_median
+      : key.startsWith('total_')
+        ? row.total_median_ns ?? row.total_p50_ns
+        : null;
+
+  // Shape stats: ratio to own median
+  const vsOwnMed =
+    key === 'ops_std' ||
+    key === 'ops_p95' ||
+    key === 'ops_p99' ||
+    key === 'total_std_ns' ||
+    key === 'total_p95_ns' ||
+    key === 'total_p99_ns';
+
+  if (vsOwnMed) {
+    // ×med is distribution shape (tail/spread vs typical), not better/worse vs baseline.
+    // Never green/red these: P95/P99 are almost always > median, so coloring was nonsense.
     if (
-      (otherTime <= gTime && otherSize < gSize) ||
-      (otherTime < gTime && otherSize <= gSize)
+      ownMedian == null ||
+      typeof ownMedian !== 'number' ||
+      !Number.isFinite(ownMedian) ||
+      ownMedian === 0
     ) {
-      return true;
+      return {
+        text: formatRosterCell(key, v, scales),
+        className: 'num' + (isBaseline ? ' baseline-col' : ''),
+      };
     }
+    const rel = formatRelativeCell(v, ownMedian, null, scales, key, 'med');
+    return {
+      text: rel.text,
+      className: 'num rel-neutral' + (isBaseline ? ' baseline-col' : ''),
+    };
+  }
+
+  // Median & size only: vs baseline (green = better, red = worse)
+  if (isBaseline || !baselineGroup) {
+    return {
+      text: formatRosterCell(key, v, scales),
+      className: 'num' + (isBaseline ? ' baseline-col' : ''),
+    };
+  }
+  const baseVal = baselineGroup[key];
+  if (baseVal == null || typeof baseVal !== 'number' || !Number.isFinite(baseVal)) {
+    return { text: formatRosterCell(key, v, scales), className: 'num' };
   }
-  return false;
+  // Equal within ~1%: treat as neutral (avoid noisy green/red on ties)
+  const ratio = v / baseVal;
+  if (Math.abs(ratio - 1) < 0.01) {
+    return {
+      text: formatRelativeCell(v, baseVal, null, scales, key, 'base').text,
+      className: 'num rel-neutral',
+    };
+  }
+  return formatRelativeCell(v, baseVal, higherIsBetter, scales, key, 'base');
+}
+
+function isParetoDominated(g, groups) {
+  const gOps = g.avg_ops_per_sec;
+  const gSize = g.median_size_bytes;
+  if (gOps == null || gSize == null) return true;
+  return groups.some((other) => {
+    if (other === g) return false;
+    const oOps = other.avg_ops_per_sec;
+    const oSize = other.median_size_bytes;
+    if (oOps == null || oSize == null) return false;
+    const betterOrEqualOps = oOps >= gOps;
+    const betterOrEqualSize = oSize <= gSize;
+    const strictlyBetter = oOps > gOps || oSize < gSize;
+    return betterOrEqualOps && betterOrEqualSize && strictlyBetter;
+  });
 }
 
 function paretoOptimalGroups(groups) {
@@ -787,169 +2163,200 @@ function paretoOptimalGroups(groups) {
 }
 
 function calculateParetoFrontier() {
-  state.paretoSerializerNames = paretoOptimalGroups(state.filteredGroups).map(
-    (g) => g.serializer
-  );
+  state.paretoSerializerNames = paretoOptimalGroups(state.filteredGroups).map((g) => g.serializer);
 }
 
-// ---------- Cross-language comparison ----------
-
-function languageLabel(langId) {
-  return LANGUAGE_CATALOG.find((l) => l.id === langId)?.label || langId;
-}
+// ---------- Cross-language ----------
 
-/** Normalize mode labels across languages (bytes/string vs stream/Stream). */
 function normalizeMode(mode) {
-  const s = String(mode || '').toLowerCase();
-  if (s === 'stream') return 'stream';
-  if (s === 'bytes' || s === 'string' || s === 'buffer') return 'bytes';
-  return s;
+  const m = String(mode || '').toLowerCase();
+  if (m === 'string' || m === 'bytes' || m === 'byte') return 'bytes';
+  if (m === 'stream') return 'stream';
+  return m;
 }
 
 function modeDisplayLabel(norm) {
-  if (norm === 'bytes') return 'bytes (buffer)';
+  if (norm === 'bytes') return 'bytes / string';
   if (norm === 'stream') return 'stream';
-  return norm;
+  return norm || '—';
 }
 
-async function fetchStatsGroups(langId) {
-  // Prefer plain JSON (no gzip edge cases); fall back to packed gz used by main dash.
-  const urls = [`data/stats_${langId}_latest.json`, `data/${langId}_latest.json.gz`];
+/**
+ * Load multi-policy groups for one language (cross-lang compare).
+ * @returns {Promise<Record<string, object[]>>} policy → groups
+ */
+async function fetchStatsGroupsByPolicy(langId) {
+  const urls = [
+    `data/stats_${langId}_latest.json.gz`,
+    `data/stats_${langId}_latest.json`,
+    `data/${langId}_latest.json.gz`,
+  ];
   for (const url of urls) {
     try {
-      const response = await fetch(url);
-      if (!response.ok) continue;
-
-      let payload;
-      try {
-        payload = await response.clone().json();
-      } catch {
-        const ds = new DecompressionStream('gzip');
-        const text = await new Response(response.body.pipeThrough(ds)).text();
-        payload = JSON.parse(text);
+      const payload = await fetchJsonMaybeGzip(url);
+      if (!payload) continue;
+      // standalone stats file vs language pack with embedded .stats
+      const statsObj =
+        payload.groups || payload.groups_by_policy || payload.default_filter_policy
+          ? payload
+          : payload.stats || payload;
+      const { groupsByPolicy, defaultPolicy } = normalizeStatsPayload(statsObj);
+      if (!Object.keys(groupsByPolicy).length) continue;
+      const stamped = {};
+      for (const [pid, list] of Object.entries(groupsByPolicy)) {
+        stamped[pid] = list.map((g) => ({
+          ...g,
+          language: g.language || langId,
+          test_data: fixtureKey(g),
+        }));
       }
-
-      const groups = payload.groups || payload.stats?.groups || [];
-      if (Array.isArray(groups) && groups.length) {
-        // Normalize fixture keys so cross-lang filters match type@n=N options
-        return groups.map((g) => ({
+      if (!stamped[defaultPolicy] && Array.isArray(statsObj.groups) && !statsObj.groups[0]?.variants) {
+        stamped[defaultPolicy] = (statsObj.groups || []).map((g) => ({
           ...g,
           language: g.language || langId,
           test_data: fixtureKey(g),
         }));
       }
+      return stamped;
     } catch (e) {
       console.warn(`Cross-lang load failed for ${langId} via ${url}:`, e);
     }
   }
-  return [];
+  return {};
+}
+
+function rebuildCrossLangForPolicy() {
+  const pid = state.filterPolicy;
+  const byLang = {};
+  for (const [lang, byPolicy] of Object.entries(state.crossLangGroupsByLangPolicy || {})) {
+    byLang[lang] =
+      byPolicy[pid] ||
+      byPolicy[state.defaultFilterPolicy] ||
+      byPolicy[DEFAULT_FILTER_POLICY] ||
+      byPolicy[Object.keys(byPolicy)[0]] ||
+      [];
+  }
+  state.crossLangGroupsByLang = byLang;
+  if (state.xlSelectionMode === 'pareto') {
+    applyCrossLangParetoSelection();
+  } else {
+    pruneCrossLangSelection();
+  }
+  updateXlBaselineSelect();
 }
 
-async function loadAllLanguagesForCrossCompare() {
+async function ensureCrossLangLoaded() {
+  if (state.crossLangLoaded) {
+    rebuildCrossLangForPolicy();
+    initCrossLangControls();
+    return;
+  }
+  showNotification('Loading cross-language stats…', 'info');
   const entries = await Promise.all(
-    LANGUAGE_CATALOG.map(async (lang) => [lang.id, await fetchStatsGroups(lang.id)])
+    LANGUAGE_CATALOG.map(async (lang) => [lang.id, await fetchStatsGroupsByPolicy(lang.id)])
   );
-  state.crossLangGroupsByLang = Object.fromEntries(entries);
-
-  const loaded = entries.filter(([, g]) => g.length > 0).map(([id]) => id);
-  if (loaded.length === 0) {
-    console.warn('No cross-language stats loaded.');
-  }
-
+  state.crossLangGroupsByLangPolicy = Object.fromEntries(entries);
+  state.crossLangLoaded = true;
+  rebuildCrossLangForPolicy();
   initCrossLangControls();
   if (state.xlSelectionMode === 'pareto' || state.xlSelected.length === 0) {
     applyCrossLangParetoSelection();
   } else {
     pruneCrossLangSelection();
-    if (state.xlSelected.length === 0) {
-      applyCrossLangParetoSelection();
-    }
   }
   renderCrossLangSelection();
-  renderCrossLangTable();
-  updateCrossLangBadge();
-  saveSettings();
+  updateXlBaselineSelect();
 }
 
 function allCrossLangGroups() {
   return Object.values(state.crossLangGroupsByLang).flat();
 }
 
-/** How many catalog languages have at least one group in this (normalized) mode. */
-function languageCountForMode(mode) {
-  if (!mode) return 0;
-  return LANGUAGE_CATALOG.filter((lang) => {
-    const groups = state.crossLangGroupsByLang[lang.id] || [];
-    return groups.some((g) => normalizeMode(g.mode) === mode);
-  }).length;
-}
-
 function initCrossLangControls() {
   const all = allCrossLangGroups();
-  // Groups normalized with fixtureKey on load; suite fixtures only
-  const testDataOptions = [
-    ...new Set(
-      all
-        .map((g) => fixtureKey(g))
-        .filter((k) => k && SUITE_TYPE_IDS.includes(baseTypeId(k)))
-    ),
-  ].sort();
-  const modeOptions = [...new Set(all.map((g) => normalizeMode(g.mode)).filter(Boolean))].sort();
-
-  populateSelect('xl-data-select', testDataOptions);
-  const modeSel = document.getElementById('xl-mode-select');
-  modeSel.innerHTML = '';
-  modeOptions.forEach((m) => {
-    const opt = document.createElement('option');
-    opt.value = m;
-    opt.textContent = modeDisplayLabel(m);
-    modeSel.appendChild(opt);
+  const discovered = discoverFixtureOptions(all);
+  const dataTypes = discovered.all;
+  const modes = [...new Set(all.map((g) => normalizeMode(g.mode)).filter(Boolean))].sort();
+
+  // Same grouped options as top toolbar Test Data (natural + compounds)
+  populateFixtureSelect(dataTypes, {
+    selectId: 'xl-data-select',
+    previous: state.xlTestData,
   });
 
-  // Prefer message@n=1; drop stale localStorage / doubled labels (e.g. type@n=100@n=100)
-  if (!testDataOptions.includes(state.xlTestData)) {
-    state.xlTestData = pickPreferredFixture(testDataOptions);
+  const modeSel = document.getElementById('xl-mode-select');
+  if (modeSel) {
+    modeSel.innerHTML = '';
+    modes.forEach((m) => {
+      const opt = document.createElement('option');
+      opt.value = m;
+      opt.textContent = modeDisplayLabel(m);
+      modeSel.appendChild(opt);
+    });
   }
 
-  // Prefer a mode available in as many languages as possible (bytes). Stream exists
-  // only for C/C# today — keep it selectable, but don't restore it as default when
-  // it would hide every other language on load.
-  const bytesCount = languageCountForMode('bytes');
-  const currentCount = languageCountForMode(state.xlMode);
-  if (
-    !modeOptions.includes(state.xlMode) ||
-    !state.xlMode ||
-    (bytesCount > currentCount && modeOptions.includes('bytes'))
-  ) {
-    state.xlMode = modeOptions.includes('bytes')
-      ? 'bytes'
-      : modeOptions[0] || '';
+  if (!dataTypes.includes(state.xlTestData)) {
+    state.xlTestData =
+      pickPreferredFixture(discovered.natural) || dataTypes[0] || '';
   }
+  if (!modes.includes(state.xlMode)) {
+    state.xlMode = modes.includes('bytes') ? 'bytes' : modes[0] || '';
+  }
+  const xd = document.getElementById('xl-data-select');
+  const xm = document.getElementById('xl-mode-select');
+  if (xd && [...xd.options].some((o) => o.value === state.xlTestData)) {
+    xd.value = state.xlTestData;
+  } else if (xd && xd.options.length) {
+    const first = [...xd.options].find((o) => !o.disabled && o.value);
+    if (first) {
+      xd.value = first.value;
+      state.xlTestData = first.value;
+    }
+  }
+  if (xm) xm.value = state.xlMode;
 
-  document.getElementById('xl-data-select').value = state.xlTestData;
-  modeSel.value = state.xlMode;
-
-  // Language add picker
   const langSel = document.getElementById('xl-add-lang');
-  langSel.innerHTML = '';
-  LANGUAGE_CATALOG.forEach((lang) => {
-    const groups = state.crossLangGroupsByLang[lang.id] || [];
-    if (!groups.length) return;
-    const opt = document.createElement('option');
-    opt.value = lang.id;
-    opt.textContent = lang.label;
-    langSel.appendChild(opt);
-  });
-
+  if (langSel) {
+    langSel.innerHTML = '';
+    LANGUAGE_CATALOG.forEach((l) => {
+      const opt = document.createElement('option');
+      opt.value = l.id;
+      opt.textContent = l.label;
+      langSel.appendChild(opt);
+    });
+  }
   refreshCrossLangAddSerializerOptions();
 }
 
+/**
+ * Resolve groups for one language under XL Test Data + Mode
+ * (supports natural, batch compound, all@1/all@100, all@all).
+ */
 function filterGroupsForCrossLang(groups) {
-  return groups.filter(
-    (g) =>
-      fixtureKey(g) === state.xlTestData &&
-      normalizeMode(g.mode) === state.xlMode
+  const modeNorm = state.xlMode;
+  const modeGroups = (groups || []).filter(
+    (g) => normalizeMode(g.mode) === modeNorm
   );
+  // Normalize mode field so builders can match with exact equality
+  const normalized = modeGroups.map((g) => ({ ...g, mode: modeNorm }));
+
+  const sel = parseFixtureSelection(state.xlTestData);
+  if (sel.kind === 'batch_compound') {
+    return buildCompoundedFixtureGroups(
+      normalized,
+      sel.base,
+      sel.nA,
+      sel.nB,
+      modeNorm
+    );
+  }
+  if (sel.kind === 'all_n') {
+    return buildAllTypesAtNGroups(normalized, sel.n, modeNorm);
+  }
+  if (sel.kind === 'all_all') {
+    return buildAllAllGroups(normalized, modeNorm);
+  }
+  return normalized.filter((g) => g.test_data === state.xlTestData);
 }
 
 function findCrossLangGroup(lang, serializer) {
@@ -957,29 +2364,24 @@ function findCrossLangGroup(lang, serializer) {
   return groups.find((g) => g.serializer === serializer) || null;
 }
 
-/** Max Pareto picks auto-selected per language in the cross-language diagram. */
-const XL_PARETO_MAX_PER_LANG = 2;
-
 function applyCrossLangParetoSelection() {
   const selected = [];
   for (const lang of LANGUAGE_CATALOG) {
     const groups = filterGroupsForCrossLang(state.crossLangGroupsByLang[lang.id] || []);
-    if (!groups.length) continue;
-    const pareto = paretoOptimalGroups(groups);
-    // Stable order: fastest total first; cap so the diagram stays readable.
-    pareto
-      .slice()
-      .sort(
-        (a, b) =>
-          (a.avg_time_total_ns ?? Infinity) - (b.avg_time_total_ns ?? Infinity)
-      )
-      .slice(0, XL_PARETO_MAX_PER_LANG)
-      .forEach((g) => {
-        selected.push({ lang: lang.id, serializer: g.serializer });
-      });
+    const pareto = paretoOptimalGroups(groups)
+      .sort((a, b) => b.avg_ops_per_sec - a.avg_ops_per_sec)
+      .slice(0, 2);
+    pareto.forEach((g) => selected.push({ lang: lang.id, serializer: g.serializer }));
   }
-  state.xlSelected = selected;
+  // Prefer diversity but keep table readable
+  state.xlSelected = selected.slice(0, MAX_COMPARE_COLUMNS);
   state.xlSelectionMode = 'pareto';
+  if (state.xlSelected.length) {
+    const keys = new Set(state.xlSelected.map((x) => `${x.lang}|${x.serializer}`));
+    if (!keys.has(state.xlBaselineKey)) {
+      state.xlBaselineKey = `${state.xlSelected[0].lang}|${state.xlSelected[0].serializer}`;
+    }
+  }
 }
 
 function pruneCrossLangSelection() {
@@ -987,513 +2389,752 @@ function pruneCrossLangSelection() {
 }
 
 function refreshCrossLangAddSerializerOptions() {
-  const lang = document.getElementById('xl-add-lang').value;
+  const lang = document.getElementById('xl-add-lang')?.value;
   const serSel = document.getElementById('xl-add-serializer');
-  serSel.innerHTML = '';
-
+  if (!serSel || !lang) return;
   const groups = filterGroupsForCrossLang(state.crossLangGroupsByLang[lang] || []);
   const names = [...new Set(groups.map((g) => g.serializer))].sort((a, b) =>
     a.localeCompare(b)
   );
+  const selected = new Set(
+    state.xlSelected.filter((x) => x.lang === lang).map((x) => x.serializer)
+  );
+  serSel.innerHTML = '';
+  names
+    .filter((n) => !selected.has(n))
+    .forEach((n) => {
+      const g = groups.find((x) => x.serializer === n);
+      const opt = document.createElement('option');
+      opt.value = n;
+      opt.textContent = g ? serializerLabelFromGroup(g) : n;
+      serSel.appendChild(opt);
+    });
+}
 
-  if (!names.length) {
-    const opt = document.createElement('option');
-    opt.value = '';
-    opt.textContent = '— no serializers —';
-    serSel.appendChild(opt);
-    return;
+/**
+ * Build a chip element: neutral pill, optional baseline highlight, truncated label.
+ */
+function makeChip({ fullLabel, shortLabel, title, isBaseline, onRemove }) {
+  const chip = document.createElement('span');
+  chip.className = 'xl-chip' + (isBaseline ? ' chip-baseline' : '');
+  chip.title = title || fullLabel;
+
+  const label = document.createElement('span');
+  label.className = 'xl-chip-label';
+  // Prefer compact shortLabel (no version in chip; full string in title)
+  if (shortLabel) {
+    label.textContent = shortLabel + (isBaseline ? ' · base' : '');
+  } else {
+    const colon = fullLabel.lastIndexOf(':');
+    if (colon > 0 && colon < fullLabel.length - 1 && !fullLabel.includes(' / ')) {
+      label.textContent = fullLabel.slice(0, colon) + (isBaseline ? ' · base' : '');
+    } else {
+      label.textContent = fullLabel + (isBaseline ? ' · base' : '');
+    }
   }
+  chip.appendChild(label);
 
-  names.forEach((name) => {
-    const opt = document.createElement('option');
-    opt.value = name;
-    opt.textContent = name;
-    serSel.appendChild(opt);
-  });
+  const btn = document.createElement('button');
+  btn.type = 'button';
+  btn.className = 'xl-chip-remove';
+  btn.textContent = '×';
+  btn.setAttribute('aria-label', `Remove ${fullLabel}`);
+  btn.addEventListener('click', onRemove);
+  chip.appendChild(btn);
+  return chip;
 }
 
-function updateCrossLangBadge() {
-  const badge = document.getElementById('cross-lang-badge');
-  if (!badge) return;
-  if (state.xlSelectionMode === 'pareto') {
-    badge.textContent = 'Pareto best';
-    badge.className = 'badge badge-cyan';
-  } else {
-    badge.textContent = 'Custom selection';
-    badge.className = 'badge badge-purple';
+/**
+ * Flat chip stream (single dense line with horizontal scroll in compact UI).
+ * groups: { langLabel?, chips: HTMLElement[] }[]
+ */
+function renderChipGroups(host, groups) {
+  host.innerHTML = '';
+  host.className = 'chip-groups chip-groups-compact';
+  if (!groups.length) {
+    const empty = document.createElement('span');
+    empty.className = 'chip-empty';
+    empty.textContent = 'None selected';
+    host.appendChild(empty);
+    return;
   }
+  // Flatten: one continuous flex row of chips (lang prefix already on chip label when needed)
+  groups.forEach((g) => {
+    g.chips.forEach((c) => host.appendChild(c));
+  });
 }
 
 function renderCrossLangSelection() {
   const host = document.getElementById('xl-selection-chips');
   if (!host) return;
-  host.innerHTML = '';
-
-  updateCrossLangBadge();
-
   if (!state.xlSelected.length) {
-    const empty = document.createElement('span');
-    empty.style.color = 'var(--text-muted)';
-    empty.style.fontSize = '0.85rem';
-    empty.textContent = 'No serializers selected. Reset to Pareto best or add one.';
-    host.appendChild(empty);
+    renderChipGroups(host, []);
+    updateCompareStatusLine();
     return;
   }
 
-  // Annotate which are currently Pareto under the active filters
-  const paretoKeys = new Set();
-  for (const lang of LANGUAGE_CATALOG) {
-    const groups = filterGroupsForCrossLang(state.crossLangGroupsByLang[lang.id] || []);
-    paretoOptimalGroups(groups).forEach((g) => {
-      paretoKeys.add(`${lang.id}|${g.serializer}`);
-    });
-  }
-
-  state.xlSelected.forEach((item, idx) => {
-    const key = `${item.lang}|${item.serializer}`;
-    const chip = document.createElement('span');
-    chip.className = 'xl-chip' + (paretoKeys.has(key) ? ' pareto-chip' : '');
-    chip.title = paretoKeys.has(key)
-      ? 'On Pareto front for this language / filter'
-      : 'Not on Pareto front for this language / filter';
-
-    const label = document.createElement('span');
-    label.className = 'xl-chip-label';
-    label.textContent = `${languageLabel(item.lang)} · ${item.serializer}`;
-
-    const remove = document.createElement('button');
-    remove.type = 'button';
-    remove.className = 'xl-chip-remove';
-    remove.setAttribute('aria-label', `Remove ${item.serializer}`);
-    remove.textContent = '×';
-    remove.addEventListener('click', () => {
-      state.xlSelectionMode = 'custom';
-      state.xlSelected = state.xlSelected.filter((_, i) => i !== idx);
-      renderCrossLangSelection();
-      renderCrossLangTable();
-      saveSettings();
-    });
-
-    chip.appendChild(label);
-    chip.appendChild(remove);
-    host.appendChild(chip);
+  // Group by language, preserve LANGUAGE_CATALOG order
+  const byLang = new Map();
+  state.xlSelected.forEach((x) => {
+    if (!byLang.has(x.lang)) byLang.set(x.lang, []);
+    byLang.get(x.lang).push(x);
   });
-}
 
-function renderCrossLangTable() {
-  const thead = document.getElementById('xl-compare-head');
-  const tbody = document.getElementById('xl-compare-body');
-  if (!thead || !tbody) return;
-
-  thead.innerHTML = '';
-  tbody.innerHTML = '';
+  const groups = [];
+  const orderedLangs = [
+    ...LANGUAGE_CATALOG.map((l) => l.id).filter((id) => byLang.has(id)),
+    ...[...byLang.keys()].filter((id) => !LANGUAGE_CATALOG.some((l) => l.id === id)),
+  ];
 
-  const headerRow = document.createElement('tr');
-  const metricTh = document.createElement('th');
-  metricTh.textContent = 'Metric';
-  headerRow.appendChild(metricTh);
+  orderedLangs.forEach((langId) => {
+    const items = byLang.get(langId) || [];
+    const langShort = languageLabel(langId);
+    const chips = items.map((x) => {
+      const g = findCrossLangGroup(x.lang, x.serializer);
+      const serLabel = g ? serializerLabelFromGroup(g) : x.serializer;
+      const key = `${x.lang}|${x.serializer}`;
+      // Compact: "C#: BinaryPack" on one chip (no separate language rows)
+      return makeChip({
+        fullLabel: serLabel,
+        shortLabel: `${langShort}: ${serLabel.split(':')[0]}`,
+        title: `${langShort} / ${serLabel}`,
+        isBaseline: key === state.xlBaselineKey,
+        onRemove: () => {
+          state.xlSelectionMode = 'custom';
+          state.xlSelected = state.xlSelected.filter(
+            (y) => !(y.lang === x.lang && y.serializer === x.serializer)
+          );
+          renderCrossLangSelection();
+          updateXlBaselineSelect();
+          refreshCrossLangAddSerializerOptions();
+          renderCompareMatrix();
+          saveSettings();
+          updateCompareStatusLine();
+        },
+      });
+    });
+    groups.push({ langLabel: langShort, chips });
+  });
 
-  const columns = state.xlSelected.map((item) => ({
-    ...item,
-    group: findCrossLangGroup(item.lang, item.serializer),
-  }));
+  renderChipGroups(host, groups);
+  updateCompareStatusLine();
+}
 
-  columns.forEach((col) => {
-    const th = document.createElement('th');
-    th.innerHTML = `<span class="xl-col-lang">${escapeHtml(languageLabel(col.lang))}</span><span class="xl-col-name">${escapeHtml(col.serializer)}</span>`;
-    headerRow.appendChild(th);
+function populateSameSerAddSelect() {
+  const sel = document.getElementById('same-ser-add-select');
+  if (!sel) return;
+  const q = (document.getElementById('same-ser-search')?.value || '').toLowerCase().trim();
+  const selected = new Set(state.detailSerializers);
+  const candidates = state.serializerNames.filter((n) => !selected.has(n));
+  const filtered = candidates.filter((n) => {
+    if (!q) return true;
+    const g = groupForSerializer(n);
+    const label = (g ? serializerLabelFromGroup(g) : n).toLowerCase();
+    return n.toLowerCase().includes(q) || label.includes(q);
   });
-  thead.appendChild(headerRow);
-
-  if (!columns.length) {
-    const tr = document.createElement('tr');
-    tr.innerHTML =
-      '<td colspan="1" style="text-align:center;color:var(--text-muted);">Select serializers to compare across languages</td>';
-    tbody.appendChild(tr);
+  sel.innerHTML = '';
+  if (!filtered.length) {
+    const opt = document.createElement('option');
+    opt.value = '';
+    opt.textContent = q ? 'No matches' : 'All selected';
+    sel.appendChild(opt);
     return;
   }
+  filtered.forEach((n) => {
+    const g = groupForSerializer(n);
+    const opt = document.createElement('option');
+    opt.value = n;
+    opt.textContent = g ? serializerLabelFromGroup(g) : n;
+    sel.appendChild(opt);
+  });
+}
 
-  CROSS_LANG_METRICS.forEach((metric) => {
-    // Skip metric row if every column is missing that field entirely
-    const values = columns.map((c) =>
-      c.group && c.group[metric.key] != null ? Number(c.group[metric.key]) : null
-    );
-    if (values.every((v) => v === null || Number.isNaN(v))) return;
+function addSameLanguageSerializer(name) {
+  if (!name || !state.serializerNames.includes(name)) return;
+  if (state.detailSerializers.includes(name)) {
+    showNotification('Already selected.', 'info');
+    return;
+  }
+  if (state.detailSerializers.length >= MAX_COMPARE_COLUMNS) {
+    showNotification(`At most ${MAX_COMPARE_COLUMNS} serializers in Compare.`, 'info');
+    return;
+  }
+  state.detailSerializers = [...state.detailSerializers, name];
+  saveSettings();
+  renderSameSelectionChips();
+  populateSameSerAddSelect();
+  renderCompareMatrix();
+  updateCompareStatusLine();
+}
 
-    let bestVal = null;
-    if (metric.higherIsBetter === true || metric.higherIsBetter === false) {
-      values.forEach((v) => {
-        if (v === null || Number.isNaN(v)) return;
+function renderSameSelectionChips() {
+  const host = document.getElementById('same-selection-chips');
+  if (!host) return;
+  const names = state.detailSerializers.filter((s) => state.serializerNames.includes(s));
+  if (!names.length) {
+    renderChipGroups(host, []);
+    updateCompareStatusLine();
+    return;
+  }
+  const chips = names.map((name) => {
+    const g = groupForSerializer(name);
+    const full = g ? serializerLabelFromGroup(g) : name;
+    return makeChip({
+      fullLabel: full,
+      shortLabel: full.split(':')[0],
+      title: full,
+      isBaseline: name === state.compareBaseline,
+      onRemove: () => {
+        state.detailSerializers = state.detailSerializers.filter((s) => s !== name);
         if (
-          bestVal === null ||
-          (metric.higherIsBetter ? v > bestVal : v < bestVal)
+          state.compareBaseline === name ||
+          !state.detailSerializers.includes(state.compareBaseline)
         ) {
-          bestVal = v;
+          state.compareBaseline = state.detailSerializers[0] || '';
+          populateBaselineSelect();
         }
-      });
-    }
-
-    const tr = document.createElement('tr');
-    const tdLabel = document.createElement('td');
-    tdLabel.textContent = metric.label;
-    tr.appendChild(tdLabel);
-
-    values.forEach((v) => {
-      const td = document.createElement('td');
-      if (v === null || Number.isNaN(v)) {
-        td.textContent = '—';
-        td.className = 'xl-missing';
-      } else {
-        td.textContent = formatMetricValue(metric.key, v);
-        // Highlight every column that ties for best (not only the first).
-        if (bestVal !== null && v === bestVal) td.classList.add('xl-best');
-      }
-      tr.appendChild(td);
+        saveSettings();
+        renderSameSelectionChips();
+        populateSameSerAddSelect();
+        renderCompareMatrix();
+        updateCompareStatusLine();
+      },
     });
-    tbody.appendChild(tr);
   });
+  renderChipGroups(host, [{ chips }]);
+  updateCompareStatusLine();
 }
 
-function escapeHtml(str) {
-  return String(str)
-    .replace(/&/g, '&amp;')
-    .replace(/</g, '&lt;')
-    .replace(/>/g, '&gt;')
-    .replace(/"/g, '&quot;');
+function updateXlBaselineSelect() {
+  const sel = document.getElementById('compare-xl-baseline-select');
+  if (!sel) return;
+  sel.innerHTML = '';
+  state.xlSelected.forEach((x) => {
+    const opt = document.createElement('option');
+    opt.value = `${x.lang}|${x.serializer}`;
+    const g = findCrossLangGroup(x.lang, x.serializer);
+    const serLabel = g ? serializerLabelFromGroup(g) : x.serializer;
+    opt.textContent = `${languageLabel(x.lang)} / ${serLabel}`;
+    sel.appendChild(opt);
+  });
+  if (
+    state.xlBaselineKey &&
+    state.xlSelected.some((x) => `${x.lang}|${x.serializer}` === state.xlBaselineKey)
+  ) {
+    sel.value = state.xlBaselineKey;
+  } else if (state.xlSelected.length) {
+    state.xlBaselineKey = `${state.xlSelected[0].lang}|${state.xlSelected[0].serializer}`;
+    sel.value = state.xlBaselineKey;
+  } else {
+    state.xlBaselineKey = '';
+  }
+}
+
+// ---------- KPIs / tables ----------
+
+function setKpiEmpty(msg) {
+  document.getElementById('kpi-total').textContent = '0';
+  document.getElementById('kpi-fastest').textContent = msg || 'No data for this filter';
+  document.getElementById('kpi-fastest-val').textContent = 'Select another data type or mode';
+  document.getElementById('kpi-compact').textContent = msg || 'No data for this filter';
+  document.getElementById('kpi-compact-val').textContent = 'Select another data type or mode';
+  document.getElementById('kpi-pareto').textContent = '—';
 }
 
-// Update KPI cards
 function updateKPIs() {
   const total = state.filteredGroups.length;
-  document.getElementById('kpi-total').textContent = total;
+  document.getElementById('kpi-total').textContent = formatIntGrouped(total);
 
   if (total === 0) {
-    document.getElementById('kpi-fastest').textContent = '-';
-    document.getElementById('kpi-fastest-val').textContent = 'Speed: -';
-    document.getElementById('kpi-compact').textContent = '-';
-    document.getElementById('kpi-compact-val').textContent = 'Size: -';
-    document.getElementById('kpi-pareto').textContent = '-';
+    setKpiEmpty('No data for this filter');
     return;
   }
 
-  // Find Fastest (min avg_time_total_ns)
-  const fastest = [...state.filteredGroups].sort((a, b) => a.avg_time_total_ns - b.avg_time_total_ns)[0];
-  document.getElementById('kpi-fastest').textContent = fastest.serializer;
-  document.getElementById('kpi-fastest-val').textContent = `Total: ${formatTime(fastest.avg_time_total_ns)} (${formatOps(fastest.avg_ops_per_sec)})`;
-
-  // Find Most Compact (min median_size_bytes)
-  const compact = [...state.filteredGroups].sort((a, b) => a.median_size_bytes - b.median_size_bytes)[0];
-  document.getElementById('kpi-compact').textContent = compact.serializer;
-  document.getElementById('kpi-compact-val').textContent = `Size: ${compact.median_size_bytes} Bytes`;
-
-  // Pareto optimal count
-  document.getElementById('kpi-pareto').textContent = `${state.paretoSerializerNames.length} / ${total}`;
-}
-
-// Compare Selectors setup
-function populateCompareSelectors() {
-  const selA = document.getElementById('compare-a-select');
-  const selB = document.getElementById('compare-b-select');
-
-  selA.innerHTML = '';
-  selB.innerHTML = '';
-
-  state.serializerNames.forEach(name => {
-    const optA = document.createElement('option');
-    const optB = document.createElement('option');
-    optA.value = optA.textContent = name;
-    optB.value = optB.textContent = name;
-    selA.appendChild(optA);
-    selB.appendChild(optB);
-  });
-
-  if (state.serializerNames.length === 0) {
-    state.compareA = '';
-    state.compareB = '';
-    return;
+  const latencyKey = (g) =>
+    g.total_median_ns != null && Number.isFinite(g.total_median_ns)
+      ? g.total_median_ns
+      : g.avg_time_total_ns;
+
+  const fastest = [...state.filteredGroups]
+    .filter((g) => latencyKey(g) != null && Number.isFinite(latencyKey(g)))
+    .sort((a, b) => latencyKey(a) - latencyKey(b))[0];
+  if (fastest) {
+    document.getElementById('kpi-fastest').textContent = fastest.serializer;
+    const lat = latencyKey(fastest);
+    const suffix = fastest.compounded ? ` · ${state.currentTestData}` : '';
+    document.getElementById('kpi-fastest-val').textContent =
+      `${formatTimeCompact(lat)} · ${formatOpsCompact(fastest.avg_ops_per_sec)}${suffix}`;
   }
 
-  // Prefer previously chosen serializers when still present
-  if (!state.serializerNames.includes(state.compareA)) {
-    state.compareA = state.serializerNames[0];
+  const compact = [...state.filteredGroups]
+    .filter((g) => g.median_size_bytes != null)
+    .sort((a, b) => a.median_size_bytes - b.median_size_bytes)[0];
+  if (compact) {
+    document.getElementById('kpi-compact').textContent = compact.serializer;
+    const suffix = compact.compounded ? ` · ${state.currentTestData}` : '';
+    document.getElementById('kpi-compact-val').textContent =
+      `${formatIntGrouped(compact.median_size_bytes)} bytes${suffix}`;
   }
-  if (!state.serializerNames.includes(state.compareB)) {
-    state.compareB = state.serializerNames[Math.min(1, state.serializerNames.length - 1)];
-  }
-
-  selA.value = state.compareA;
-  selB.value = state.compareB;
-}
 
-/** Metric family for checklist + table grouping. */
-const METRIC_GROUP_ORDER = [
-  'Run & quality',
-  'Throughput',
-  'Serialization',
-  'Deserialization',
-  'Total latency',
-  'Size',
-  'Comparisons',
-  'Other',
-];
-
-function metricGroupName(key) {
-  if (
-    [
-      'runs',
-      'runs_raw',
-      'warmup_skipped',
-      'outliers_removed',
-      'serializer_version',
-      'mean_fidelity',
-      'mean_memory_peak_bytes',
-    ].includes(key)
-  ) {
-    return 'Run & quality';
-  }
-  if (
-    key.includes('ops_per_sec') ||
-    key.endsWith('_ops_mean') ||
-    key.endsWith('_ops_median') ||
-    key.endsWith('_ops_p95') ||
-    key === 'min_ops_per_sec' ||
-    key === 'max_ops_per_sec'
-  ) {
-    return 'Throughput';
+  document.getElementById('kpi-pareto').textContent =
+    `${state.paretoSerializerNames.length} / ${total}`;
+  const paretoDesc = document.querySelector('#kpi-pareto')?.closest('.kpi-card')?.querySelector('.kpi-desc');
+  if (paretoDesc) {
+    const pl =
+      state.filterPolicies[state.filterPolicy]?.label || state.filterPolicy || 'default';
+    paretoDesc.textContent = `Optimal trade-offs · samples: ${pl}`;
   }
-  if (key.startsWith('ser_') || key === 'avg_time_ser_ns') return 'Serialization';
-  if (key.startsWith('deser_') || key === 'avg_time_deser_ns') return 'Deserialization';
-  if (key.startsWith('total_') || key === 'avg_time_total_ns') return 'Total latency';
-  if (key.startsWith('size_') || key === 'median_size_bytes') return 'Size';
-  if (
-    key.includes('effect_') ||
-    key.includes('baseline') ||
-    key.includes('fastest') ||
-    key.includes('speedup')
-  ) {
-    return 'Comparisons';
+}
+
+function groupForSerializer(name) {
+  return state.filteredGroups.find((g) => g.serializer === name) || null;
+}
+
+function populateBaselineSelect() {
+  const sels = [
+    document.getElementById('compare-baseline-select'),
+    document.getElementById('roster-baseline-select'),
+  ].filter(Boolean);
+  if (!sels.length) return;
+
+  if (state.compareBaseline && state.serializerNames.includes(state.compareBaseline)) {
+    // keep
+  } else if (state.serializerNames.length) {
+    state.compareBaseline =
+      state.paretoSerializerNames[0] || state.serializerNames[0] || '';
   }
-  return 'Other';
+
+  sels.forEach((sel) => {
+    sel.innerHTML = '';
+    state.serializerNames.forEach((name) => {
+      const opt = document.createElement('option');
+      opt.value = name;
+      const g = groupForSerializer(name);
+      const label = g ? serializerLabelFromGroup(g) : name;
+      opt.textContent = label + (state.paretoSerializerNames.includes(name) ? ' ★' : '');
+      sel.appendChild(opt);
+    });
+    if (state.compareBaseline && state.serializerNames.includes(state.compareBaseline)) {
+      sel.value = state.compareBaseline;
+    }
+  });
 }
 
-/** Higher is better for highlighting multi-serializer metric rows; null = no highlight. */
 function metricHigherIsBetter(key) {
   if (
-    key.includes('cliffs_label') ||
-    key.includes('baseline_serializer') ||
-    key.includes('fastest_in_group') ||
-    key === 'serializer_version' ||
-    key.includes('cliffs_delta') ||
-    key.includes('hedges_g')
-  ) {
-    return null;
-  }
-  if (
-    key.includes('ops_per_sec') ||
-    key.endsWith('_ops_mean') ||
-    key.endsWith('_ops_median') ||
-    key.endsWith('_ops_p95') ||
-    key === 'min_ops_per_sec' ||
-    key === 'max_ops_per_sec' ||
-    key === 'mean_fidelity' ||
-    key.includes('speedup')
+    key.includes('ops') ||
+    key.includes('fidelity') ||
+    key === 'runs' ||
+    key === 'fastest_in_group'
   ) {
     return true;
   }
   if (
+    key.includes('time') ||
     key.endsWith('_ns') ||
-    key.endsWith('_bytes') ||
-    key.includes('size_') ||
-    key.endsWith('_cv') ||
-    key.includes('_var_') ||
-    key.includes('_std_') ||
-    key.includes('_mad_')
+    key.includes('size') ||
+    key.includes('bytes') ||
+    key.includes('cv') ||
+    key.includes('mad') ||
+    key.includes('std') ||
+    key.includes('memory')
   ) {
     return false;
   }
   return null;
 }
 
+function metricGroupName(key) {
+  if (key.includes('ops')) return 'Throughput';
+  if (key.startsWith('ser_') || key.includes('time_ser')) return 'Serialize';
+  if (key.startsWith('deser_') || key.includes('time_deser')) return 'Deserialize';
+  if (key.startsWith('total_') || key.includes('time_total')) return 'Total time';
+  if (key.includes('size') || key.includes('bytes') || key.includes('memory')) return 'Size & memory';
+  if (key.includes('fidelity') || key.includes('effect')) return 'Quality';
+  if (key.includes('run') || key.includes('warmup') || key.includes('outlier')) return 'Samples';
+  return 'Other';
+}
+
 function groupMetrics(keys) {
-  const buckets = new Map(METRIC_GROUP_ORDER.map((g) => [g, []]));
+  const map = new Map();
   keys.forEach((k) => {
     const g = metricGroupName(k);
-    if (!buckets.has(g)) buckets.set(g, []);
-    buckets.get(g).push(k);
+    if (!map.has(g)) map.set(g, []);
+    map.get(g).push(k);
   });
-  for (const arr of buckets.values()) arr.sort((a, b) => a.localeCompare(b));
-  return METRIC_GROUP_ORDER
-    .map((name) => ({ name, keys: buckets.get(name) || [] }))
-    .filter((g) => g.keys.length > 0);
+  return [...map.entries()].map(([name, ks]) => ({ name, keys: ks }));
 }
 
-function populateDetailSerializerSelect() {
-  // Keep only still-valid serializers; default to first if empty
-  state.detailSerializers = state.detailSerializers.filter((s) =>
-    state.serializerNames.includes(s)
-  );
-  if (state.detailSerializers.length === 0 && state.serializerNames.length > 0) {
-    state.detailSerializers = [state.serializerNames[0]];
-  }
-  renderDetailSerializerChecklist();
+function metricLabel(key) {
+  return key
+    .replace(/_ns$/g, '')
+    .replace(/_bytes$/g, '')
+    .replace(/_per_sec$/g, '')
+    .replace(/_/g, ' ');
 }
 
-function renderDetailSerializerChecklist() {
-  const container = document.getElementById('detail-serializer-checklist');
-  if (!container) return;
+function openMetricsPanel(open) {
+  const body = document.getElementById('metrics-panel-body');
+  const toggle = document.getElementById('metrics-edit-toggle');
+  if (body) body.hidden = !open;
+  if (toggle) toggle.textContent = open ? 'Custom ▴' : 'Custom ▾';
+}
 
-  container.innerHTML = '';
-  const selected = new Set(state.detailSerializers);
+function setMetricsPresetActive(preset) {
+  document.querySelectorAll('.preset-btn').forEach((btn) => {
+    btn.classList.toggle('active', btn.dataset.preset === preset);
+  });
+}
 
-  if (!state.serializerNames.length) {
-    const empty = document.createElement('span');
-    empty.style.color = 'var(--text-muted)';
-    empty.style.fontSize = '0.8rem';
-    empty.textContent = 'No serializers for this filter';
-    container.appendChild(empty);
-    return;
+function applyMetricPreset(preset) {
+  const keys = METRIC_PRESETS[preset] || METRIC_PRESETS.defaults;
+  state.selectedMetrics = keys.filter((k) => state.availableMetrics.includes(k));
+  if (!state.selectedMetrics.length && preset === 'defaults') {
+    state.selectedMetrics = state.availableMetrics.slice(0, 12);
   }
+  setMetricsPresetActive(preset);
+  // Latency/size presets leave catalog closed; custom opens it
+  openMetricsPanel(false);
+  saveSettings();
+  renderMetricsChecklist();
+  renderCompareMatrix();
+  updateCompareStatusLine();
+}
 
-  state.serializerNames.forEach((name) => {
-    const label = document.createElement('label');
-    label.className = 'metric-check-item';
-    label.title = name;
-
-    const input = document.createElement('input');
-    input.type = 'checkbox';
-    input.value = name;
-    input.checked = selected.has(name);
-    input.addEventListener('change', () => {
-      if (input.checked) {
-        if (!state.detailSerializers.includes(name)) {
-          state.detailSerializers = [...state.detailSerializers, name].sort((a, b) =>
-            a.localeCompare(b)
-          );
-        }
-      } else {
-        state.detailSerializers = state.detailSerializers.filter((s) => s !== name);
-      }
-      saveSettings();
-      renderSerializerMetricsTable();
-    });
-
-    const span = document.createElement('span');
-    span.textContent = name;
-
-    label.appendChild(input);
-    label.appendChild(span);
-    container.appendChild(label);
-  });
+/** @deprecated checklist replaced by chips; kept as no-op alias */
+function renderDetailSerializerChecklist() {
+  renderSameSelectionChips();
+  populateSameSerAddSelect();
 }
 
 function renderMetricsChecklist() {
   const container = document.getElementById('metrics-checklist');
   if (!container) return;
-
   container.innerHTML = '';
-  const selected = new Set(state.selectedMetrics);
   const groups = groupMetrics(state.availableMetrics);
-
   groups.forEach((group) => {
-    const block = document.createElement('div');
-    block.className = 'metric-group-block';
-
-    const title = document.createElement('div');
-    title.className = 'metric-group-title';
-
-    const titleText = document.createElement('span');
-    titleText.textContent = `${group.name} (${group.keys.length})`;
-
-    const groupBtn = document.createElement('button');
-    groupBtn.type = 'button';
-    groupBtn.className = 'metric-group-toggle';
-    const allOn = group.keys.every((k) => selected.has(k));
-    groupBtn.textContent = allOn ? 'Clear' : 'All';
-    groupBtn.addEventListener('click', () => {
-      if (allOn) {
-        state.selectedMetrics = state.selectedMetrics.filter((k) => !group.keys.includes(k));
-      } else {
-        const set = new Set(state.selectedMetrics);
-        group.keys.forEach((k) => set.add(k));
-        state.selectedMetrics = [...set].sort((a, b) => a.localeCompare(b));
-      }
-      saveSettings();
-      renderMetricsChecklist();
-      renderSerializerMetricsTable();
+    const selectedInGroup = group.keys.filter((k) => state.selectedMetrics.includes(k)).length;
+    const wrap = document.createElement('div');
+    wrap.className = 'metric-accordion-group';
+    if (metricAccordionOpen[group.name]) wrap.classList.add('open');
+
+    const head = document.createElement('button');
+    head.type = 'button';
+    head.className = 'metric-accordion-head';
+    head.innerHTML =
+      `<span><span class="acc-chevron">▸</span>${escapeHtml(group.name)}</span>` +
+      `<span class="acc-count">${selectedInGroup}/${group.keys.length}</span>`;
+    head.addEventListener('click', () => {
+      metricAccordionOpen[group.name] = !metricAccordionOpen[group.name];
+      wrap.classList.toggle('open', !!metricAccordionOpen[group.name]);
     });
+    wrap.appendChild(head);
 
-    title.appendChild(titleText);
-    title.appendChild(groupBtn);
-    block.appendChild(title);
-
-    const items = document.createElement('div');
-    items.className = 'metric-group-items';
-
+    const body = document.createElement('div');
+    body.className = 'metric-accordion-body';
     group.keys.forEach((key) => {
       const label = document.createElement('label');
-      label.className = 'metric-check-item';
-      label.title = key;
-
-      const input = document.createElement('input');
-      input.type = 'checkbox';
-      input.value = key;
-      input.checked = selected.has(key);
-      input.addEventListener('change', () => {
-        if (input.checked) {
+      label.className = 'metrics-check-item';
+      const cb = document.createElement('input');
+      cb.type = 'checkbox';
+      cb.checked = state.selectedMetrics.includes(key);
+      cb.addEventListener('change', () => {
+        if (cb.checked) {
           if (!state.selectedMetrics.includes(key)) {
-            state.selectedMetrics = [...state.selectedMetrics, key].sort((a, b) =>
-              a.localeCompare(b)
-            );
+            state.selectedMetrics = [...state.selectedMetrics, key];
           }
         } else {
           state.selectedMetrics = state.selectedMetrics.filter((k) => k !== key);
         }
+        setMetricsPresetActive('custom');
         saveSettings();
-        renderSerializerMetricsTable();
+        // refresh counts on heads without full re-render of open state
+        renderMetricsChecklist();
+        renderCompareMatrix();
+        updateCompareStatusLine();
       });
+      label.appendChild(cb);
+      label.appendChild(document.createTextNode(` ${metricLabel(key)}`));
+      label.title = key;
+      body.appendChild(label);
+    });
+    wrap.appendChild(body);
+    container.appendChild(wrap);
+  });
+  updateCompareStatusLine();
+}
+
+function handleTableSort(key) {
+  if (state.sortKey === key) {
+    state.sortDirection = state.sortDirection === 'asc' ? 'desc' : 'asc';
+  } else {
+    state.sortKey = key;
+    state.sortDirection = key === 'serializer' ? 'asc' : 'desc';
+  }
+  updateSortIndicators();
+  saveSettings();
+  renderTable();
+}
+
+function renderTable() {
+  const table = document.getElementById('analytics-table');
+  const tbody = document.getElementById('table-body');
+  if (!tbody) return;
+  tbody.innerHTML = '';
+
+  const isOps = state.rosterMetric === 'ops';
+  if (table) {
+    table.classList.toggle('view-ops', isOps);
+    table.classList.toggle('view-latency', !isOps);
+  }
+
+  // Enrich with derived ops stats for sort + cells
+  let rows = state.filteredGroups
+    .filter((g) => (g.serializer || '').toLowerCase().includes(state.searchQuery))
+    .map(withOpsDerivedStats);
+
+  rows.sort((a, b) => {
+    let valA = a[state.sortKey];
+    let valB = b[state.sortKey];
+    if (valA === null || valA === undefined) return 1;
+    if (valB === null || valB === undefined) return -1;
+    if (typeof valA === 'string') {
+      return state.sortDirection === 'asc'
+        ? valA.localeCompare(valB)
+        : valB.localeCompare(valA);
+    }
+    return state.sortDirection === 'asc' ? valA - valB : valB - valA;
+  });
+
+  const metricKeys = rosterMetricKeys();
+  // Scales: ops_* use ops scale; total_* use latency scale
+  const latVals = [];
+  const opsVals = [];
+  for (const g of rows) {
+    for (const { key } of metricKeys) {
+      const v = g[key];
+      if (typeof v !== 'number' || !Number.isFinite(v)) continue;
+      if (key.startsWith('ops_')) opsVals.push(v);
+      else if (key.endsWith('_ns')) latVals.push(v);
+    }
+  }
+  const scales = {
+    latency: latVals.length
+      ? chooseLatencyUnit(latVals)
+      : { unit: 'µs', divisor: 1e3, header: 'µs' },
+    ops: opsVals.length
+      ? chooseOpsUnit(opsVals)
+      : { unit: 'ops', divisor: 1, header: 'Ops/s' },
+  };
+  const u = scales.latency.header;
+  const oHdr = scales.ops.header;
+
+  // Header labels with units
+  const setTh = (id, text) => {
+    const el = document.getElementById(id);
+    if (el) el.textContent = text;
+  };
+  setTh('th-ops-median', `Median (${oHdr})`);
+  setTh('th-ops-std', `Std (${oHdr})`);
+  setTh('th-ops-p95', `P95 (${oHdr})`);
+  setTh('th-ops-p99', `P99 (${oHdr})`);
+  setTh('th-lat-median', `Median (${u})`);
+  setTh('th-lat-std', `Std (${u})`);
+  setTh('th-lat-p95', `P95 (${u})`);
+  setTh('th-lat-p99', `P99 (${u})`);
+
+  const baselineRaw =
+    state.filteredGroups.find((g) => g.serializer === state.compareBaseline) || null;
+  const baselineGroup = baselineRaw ? withOpsDerivedStats(baselineRaw) : null;
+
+  const help = document.getElementById('detailed-analytics-help');
+  if (help) {
+    const scope = parseFixtureSelection(state.currentTestData);
+    let scopeNote = ' Full roster for the current language, data type, and mode.';
+    if (scope.kind === 'batch_compound') {
+      scopeNote =
+        ` <strong>Compounded batch</strong>: mean of <code>${escapeHtml(scope.base)}@n=${scope.nA}</code> and <code>${escapeHtml(scope.base)}@n=${scope.nB}</code>.`;
+    } else if (scope.kind === 'all_n') {
+      scopeNote = ` <strong>Compounded data types</strong> at <code>n=${scope.n}</code>.`;
+    } else if (scope.kind === 'all_all') {
+      scopeNote = ` <strong>Compounded all</strong> (<code>all@all</code>).`;
+    }
+    const speedNote = isOps
+      ? ' View: <strong>Ops/s</strong> — Median, Std, P95, P99 + size.'
+      : ' View: <strong>Latency</strong> — Median, Std, P95, P99 + size.';
+    const ratioNote =
+      ' Median &amp; size: <code>×base</code> vs baseline (green better / red worse).' +
+      ' Std/P95/P99: <code>×med</code> vs that row’s median.';
+    const paretoNote = ' <span style="color:var(--color-blue)">Blue rows</span> = Pareto-optimal.';
+    if (baselineGroup) {
+      help.innerHTML =
+        scopeNote +
+        speedNote +
+        ratioNote +
+        ` Baseline: <strong>${escapeHtml(serializerLabelFromGroup(baselineGroup))}</strong>.` +
+        paretoNote;
+    } else {
+      help.innerHTML = scopeNote + speedNote + ratioNote + paretoNote;
+    }
+  }
+
+  const colCount = 1 + metricKeys.length;
+  if (rows.length === 0) {
+    const tr = document.createElement('tr');
+    tr.innerHTML = `<td colspan="${colCount}" style="text-align:center;color:var(--text-muted);">No serializers match search query</td>`;
+    tbody.appendChild(tr);
+    updateSortIndicators();
+    return;
+  }
+
+  rows.forEach((r) => {
+    const tr = document.createElement('tr');
+    const isBaseline = baselineGroup && r.serializer === baselineGroup.serializer;
+    const isOptimal = state.paretoSerializerNames.includes(r.serializer);
+    if (isBaseline) tr.classList.add('roster-baseline-row');
+    if (isOptimal) tr.classList.add('roster-pareto-row');
+
+    const tdName = document.createElement('td');
+    tdName.className = 'str';
+    const displayName = serializerLabelFromGroup(r);
+    let nameHtml = `<strong>${escapeHtml(displayName)}</strong>`;
+    if (isBaseline) {
+      nameHtml += ' <span class="badge badge-cyan">Baseline</span>';
+    }
+    tdName.innerHTML = nameHtml;
+    tdName.title = r.serializer_version
+      ? `${r.serializer} @ ${r.serializer_version}`
+      : r.serializer;
+    tr.appendChild(tdName);
 
-      const span = document.createElement('span');
-      span.textContent = metricLabel(key);
+    metricKeys.forEach(({ key, higherIsBetter }) => {
+      const td = document.createElement('td');
+      if (key.startsWith('ops_')) td.classList.add('roster-col-ops');
+      if (key.startsWith('total_')) td.classList.add('roster-col-latency');
+
+      const v = r[key];
+      if (v === null || v === undefined) {
+        td.textContent = '—';
+        td.classList.add('num', 'sm-missing');
+        tr.appendChild(td);
+        return;
+      }
 
-      label.appendChild(input);
-      label.appendChild(span);
-      items.appendChild(label);
+      const cell = formatRosterRelativeCell(r, key, higherIsBetter, scales, baselineGroup, isBaseline);
+      td.textContent = cell.text;
+      td.className = (td.className + ' ' + cell.className).trim();
+      tr.appendChild(td);
     });
 
-    block.appendChild(items);
-    container.appendChild(block);
+    tbody.appendChild(tr);
   });
+  updateSortIndicators();
 }
 
-function renderSerializerMetricsTable() {
+function renderCompareMatrix() {
   const thead = document.getElementById('serializer-metrics-head');
   const tbody = document.getElementById('serializer-metrics-body');
   if (!thead || !tbody) return;
-
   thead.innerHTML = '';
   tbody.innerHTML = '';
 
-  const serializers = state.detailSerializers.filter((s) =>
-    state.serializerNames.includes(s)
-  );
-  const columns = serializers.map((name) => ({
-    name,
-    group: state.filteredGroups.find((g) => g.serializer === name) || null,
-  }));
+  /** @type {{ key: string, label: string, group: object|null, isBaseline: boolean }[]} */
+  let columns = [];
+
+  if (state.compareScope === 'same') {
+    const names = state.detailSerializers.filter((s) => state.serializerNames.includes(s));
+    // Baseline first
+    const ordered = [];
+    if (state.compareBaseline && names.includes(state.compareBaseline)) {
+      ordered.push(state.compareBaseline);
+    }
+    names.forEach((n) => {
+      if (!ordered.includes(n)) ordered.push(n);
+    });
+    columns = ordered.map((name) => {
+      const group = state.filteredGroups.find((g) => g.serializer === name) || null;
+      return {
+        key: name,
+        // Docs Summary style: name:version
+        label: group ? serializerLabelFromGroup(group) : name,
+        group,
+        isBaseline: name === state.compareBaseline,
+      };
+    });
+  } else {
+    const ordered = [...state.xlSelected];
+    // baseline first
+    const bi = ordered.findIndex((x) => `${x.lang}|${x.serializer}` === state.xlBaselineKey);
+    if (bi > 0) {
+      const [b] = ordered.splice(bi, 1);
+      ordered.unshift(b);
+    }
+    columns = ordered.map((x) => {
+      const group = findCrossLangGroup(x.lang, x.serializer);
+      const serLabel = group
+        ? serializerLabelFromGroup(group)
+        : x.serializer;
+      return {
+        key: `${x.lang}|${x.serializer}`,
+        label: `${languageLabel(x.lang)} / ${serLabel}`,
+        group,
+        isBaseline: `${x.lang}|${x.serializer}` === state.xlBaselineKey,
+      };
+    });
+  }
 
   const headerRow = document.createElement('tr');
   const metricTh = document.createElement('th');
+  metricTh.className = 'str cmp-th-metric';
   metricTh.textContent = 'Metric';
   headerRow.appendChild(metricTh);
   columns.forEach((col) => {
     const th = document.createElement('th');
-    th.textContent = col.name;
+    th.className = 'cmp-th-ser' + (col.isBaseline ? ' baseline-col' : '');
+    th.title = col.isBaseline ? `${col.label} (baseline)` : col.label;
+
+    // Split "Lang / name:ver" or "name:ver" into stacked lines (avoids interleaved wraps)
+    let main = col.label;
+    let sub = '';
+    const slash = col.label.indexOf(' / ');
+    if (slash >= 0) {
+      sub = col.label.slice(0, slash);
+      main = col.label.slice(slash + 3);
+    }
+    const colon = main.lastIndexOf(':');
+    let name = main;
+    let ver = '';
+    if (colon > 0 && colon < main.length - 1) {
+      name = main.slice(0, colon);
+      ver = main.slice(colon + 1);
+    }
+    const nameEl = document.createElement('span');
+    nameEl.className = 'cmp-th-name';
+    nameEl.textContent = name;
+    th.appendChild(nameEl);
+    if (ver) {
+      const verEl = document.createElement('span');
+      verEl.className = 'cmp-th-ver';
+      verEl.textContent = ver;
+      th.appendChild(verEl);
+    }
+    if (sub) {
+      const subEl = document.createElement('span');
+      subEl.className = 'cmp-th-lang';
+      subEl.textContent = sub;
+      th.insertBefore(subEl, nameEl);
+    }
+    if (col.isBaseline) {
+      const baseEl = document.createElement('span');
+      baseEl.className = 'cmp-th-base';
+      baseEl.textContent = 'baseline';
+      th.appendChild(baseEl);
+    }
     headerRow.appendChild(th);
   });
   thead.appendChild(headerRow);
 
   const colCount = Math.max(1, columns.length + 1);
-
   if (!columns.length) {
     const tr = document.createElement('tr');
     tr.innerHTML = `<td colspan="${colCount}" style="text-align:center;color:var(--text-muted);">Select one or more serializers</td>`;
@@ -1501,16 +3142,30 @@ function renderSerializerMetricsTable() {
     return;
   }
 
-  const selectedKeys = state.selectedMetrics.filter((k) =>
-    state.availableMetrics.includes(k)
-  );
+  // Metrics: use selected; if cross-lang prefer known keys that exist
+  let selectedKeys = state.selectedMetrics.filter((k) => state.availableMetrics.includes(k));
+  if (state.compareScope === 'cross') {
+    // Union of keys from available metrics defaults that appear in any column
+    const crossKeys = CROSS_LANG_METRICS.map((m) => m.key).filter((k) =>
+      columns.some((c) => c.group && c.group[k] != null)
+    );
+    selectedKeys = state.selectedMetrics.length
+      ? state.selectedMetrics.filter((k) => columns.some((c) => c.group && c.group[k] != null))
+      : crossKeys;
+    if (!selectedKeys.length) selectedKeys = crossKeys;
+  }
+
   if (!selectedKeys.length) {
     const tr = document.createElement('tr');
-    tr.innerHTML = `<td colspan="${colCount}" style="text-align:center;color:var(--text-muted);">Select at least one metric in the checklist</td>`;
+    tr.innerHTML = `<td colspan="${colCount}" style="text-align:center;color:var(--text-muted);">Select at least one metric</td>`;
     tbody.appendChild(tr);
     return;
   }
 
+  const groupsForScale = columns.map((c) => c.group).filter(Boolean);
+  const scales = scalesFromGroups(groupsForScale, selectedKeys);
+  const baselineCol = columns.find((c) => c.isBaseline) || columns[0];
+
   const groups = groupMetrics(selectedKeys);
   groups.forEach((group) => {
     const groupRow = document.createElement('tr');
@@ -1522,48 +3177,33 @@ function renderSerializerMetricsTable() {
     tbody.appendChild(groupRow);
 
     group.keys.forEach((key) => {
-      const values = columns.map((c) => {
-        if (!c.group || c.group[key] === undefined || c.group[key] === null) return null;
-        const v = c.group[key];
-        return typeof v === 'number' ? v : v;
-      });
-
-      const higherIsBetter = metricHigherIsBetter(key);
-      let bestVal = null;
-      if (higherIsBetter === true || higherIsBetter === false) {
-        values.forEach((v) => {
-          if (typeof v !== 'number' || !Number.isFinite(v)) return;
-          if (
-            bestVal === null ||
-            (higherIsBetter ? v > bestVal : v < bestVal)
-          ) {
-            bestVal = v;
-          }
-        });
-      }
-
       const tr = document.createElement('tr');
       const tdKey = document.createElement('td');
-      tdKey.textContent = key;
-      tdKey.title = metricLabel(key);
+      tdKey.className = 'str';
+      tdKey.textContent = metricHeaderLabel(key, scales);
+      tdKey.title = key;
       tr.appendChild(tdKey);
 
-      values.forEach((v) => {
+      const baselineVal =
+        baselineCol?.group && baselineCol.group[key] != null ? baselineCol.group[key] : null;
+      const higherIsBetter = metricHigherIsBetter(key);
+
+      columns.forEach((col) => {
         const td = document.createElement('td');
-        if (v === null || v === undefined) {
+        const v =
+          col.group && col.group[key] !== undefined && col.group[key] !== null
+            ? col.group[key]
+            : null;
+        if (v === null) {
           td.textContent = '—';
-          td.className = 'sm-missing';
+          td.className = 'num sm-missing';
+        } else if (col.isBaseline || typeof v !== 'number' || typeof baselineVal !== 'number') {
+          td.textContent = formatMetricCell(key, v, scales);
+          td.className = 'num';
         } else {
-          td.textContent = formatMetricValue(key, v);
-          // Highlight every tied best value when comparing multiple serializers.
-          if (
-            columns.length > 1 &&
-            typeof v === 'number' &&
-            bestVal !== null &&
-            v === bestVal
-          ) {
-            td.classList.add('sm-best');
-          }
+          const rel = formatRelativeCell(v, baselineVal, higherIsBetter, scales, key);
+          td.textContent = rel.text;
+          td.className = rel.className;
         }
         tr.appendChild(td);
       });
@@ -1572,188 +3212,129 @@ function renderSerializerMetricsTable() {
   });
 }
 
-function metricLabel(key) {
-  // Short readable label for checklist; full field id stays in the table.
-  return key
-    .replace(/_ns$/g, ' (ns)')
-    .replace(/_bytes$/g, ' (B)')
-    .replace(/_per_sec$/g, '/s')
-    .replace(/_/g, ' ');
+function escapeHtml(str) {
+  return String(str)
+    .replace(/&/g, '&amp;')
+    .replace(/</g, '&lt;')
+    .replace(/>/g, '&gt;')
+    .replace(/"/g, '&quot;');
 }
 
-function formatMetricValue(key, value) {
-  if (value === null || value === undefined || value === '') return '—';
-  if (typeof value === 'boolean') return value ? 'true' : 'false';
-  if (typeof value === 'string') return value;
-
-  if (typeof value === 'number') {
-    if (!Number.isFinite(value)) return String(value);
-    if (key.endsWith('_ns')) return formatTime(value);
-    if (
-      key.includes('ops_per_sec') ||
-      key.endsWith('_ops_mean') ||
-      key.endsWith('_ops_median') ||
-      key.endsWith('_ops_p95')
-    ) {
-      return formatOps(value);
+function copyRosterMarkdown() {
+  const metricSpecs = rosterMetricKeys();
+  const rows = state.filteredGroups
+    .map(withOpsDerivedStats)
+    .sort((a, b) => a.serializer.localeCompare(b.serializer));
+  const latVals = [];
+  const opsVals = [];
+  for (const g of rows) {
+    for (const { key } of metricSpecs) {
+      const v = g[key];
+      if (typeof v !== 'number' || !Number.isFinite(v)) continue;
+      if (key.startsWith('ops_')) opsVals.push(v);
+      else if (key.endsWith('_ns')) latVals.push(v);
     }
-    if (key.endsWith('_bytes') || key.startsWith('size_')) {
-      if (Math.abs(value) >= 1000) {
-        return `${value.toLocaleString(undefined, { maximumFractionDigits: 2 })} B`;
-      }
-      return `${Number.isInteger(value) ? value : value.toFixed(4)} B`;
-    }
-    if (Number.isInteger(value)) return String(value);
-    return Number(value.toPrecision(8)).toString();
-  }
-
-  return String(value);
-}
-
-// Update Side by side comparison UI
-function updateComparison() {
-  const serializerA = state.filteredGroups.find(g => g.serializer === state.compareA);
-  const serializerB = state.filteredGroups.find(g => g.serializer === state.compareB);
-
-  if (!serializerA || !serializerB) {
-    clearComparisonUI();
-    return;
-  }
-
-  updateMetricUI('compare-total-val', 'compare-total-diff', serializerA.avg_time_total_ns, serializerB.avg_time_total_ns, 'ns', true);
-  updateMetricUI('compare-ser-val', 'compare-ser-diff', serializerA.avg_time_ser_ns, serializerB.avg_time_ser_ns, 'ns', true);
-  updateMetricUI('compare-deser-val', 'compare-deser-diff', serializerA.avg_time_deser_ns, serializerB.avg_time_deser_ns, 'ns', true);
-  updateMetricUI('compare-throughput-val', 'compare-throughput-diff', serializerA.avg_ops_per_sec, serializerB.avg_ops_per_sec, 'ops', false);
-  updateMetricUI('compare-size-val', 'compare-size-diff', serializerA.median_size_bytes, serializerB.median_size_bytes, 'bytes', true);
-}
-
-function updateMetricUI(valId, diffId, valA, valB, type, isLowerBetter) {
-  const valEl = document.getElementById(valId);
-  const diffEl = document.getElementById(diffId);
-
-  let displayA = '', displayB = '';
-  if (type === 'ns') {
-    displayA = formatTime(valA);
-    displayB = formatTime(valB);
-  } else if (type === 'ops') {
-    displayA = formatOps(valA);
-    displayB = formatOps(valB);
-  } else {
-    displayA = `${valA} B`;
-    displayB = `${valB} B`;
-  }
-
-  valEl.textContent = `${displayB}`;
-
-  if (valA === 0 || valB === 0 || valA === null || valB === null) {
-    diffEl.textContent = 'N/A';
-    diffEl.className = 'compare-diff diff-neutral';
-    return;
-  }
-
-  const pct = ((valB - valA) / valA) * 100;
-  const isBetter = isLowerBetter ? pct < 0 : pct > 0;
-  const absPct = Math.abs(pct).toFixed(1);
-
-  if (pct === 0) {
-    diffEl.textContent = 'Equal';
-    diffEl.className = 'compare-diff diff-neutral';
-  } else if (isBetter) {
-    diffEl.textContent = `-${absPct}% (Better)`;
-    diffEl.className = 'compare-diff diff-positive';
-    if (!isLowerBetter) diffEl.textContent = `+${absPct}% (Better)`;
-  } else {
-    diffEl.textContent = `+${absPct}% (Worse)`;
-    diffEl.className = 'compare-diff diff-negative';
-    if (!isLowerBetter) diffEl.textContent = `-${absPct}% (Worse)`;
   }
-}
-
-function clearComparisonUI() {
-  ['compare-total-val', 'compare-ser-val', 'compare-deser-val', 'compare-throughput-val', 'compare-size-val'].forEach(id => {
-    document.getElementById(id).textContent = '-';
+  const scales = {
+    latency: latVals.length ? chooseLatencyUnit(latVals) : { divisor: 1e3, header: 'µs' },
+    ops: opsVals.length ? chooseOpsUnit(opsVals) : { divisor: 1, header: 'Ops/s' },
+  };
+  const baselineRaw =
+    state.filteredGroups.find((g) => g.serializer === state.compareBaseline) || null;
+  const baselineGroup = baselineRaw ? withOpsDerivedStats(baselineRaw) : null;
+  const baseLabel = baselineGroup
+    ? serializerLabelFromGroup(baselineGroup)
+    : state.compareBaseline || '—';
+  const u = scales.latency.header;
+  const oHdr = scales.ops.header;
+  const headers = ['Serializer'];
+  metricSpecs.forEach(({ key, label }) => {
+    if (key.startsWith('ops_')) headers.push(`${label} (${oHdr})`);
+    else if (key.endsWith('_ns')) headers.push(`${label} (${u})`);
+    else if (key === 'median_size_bytes') headers.push('Size (bytes)');
+    else headers.push(label || key);
   });
-  ['compare-total-diff', 'compare-ser-diff', 'compare-deser-diff', 'compare-throughput-diff', 'compare-size-diff'].forEach(id => {
-    document.getElementById(id).textContent = '-';
-    document.getElementById(id).className = 'compare-diff diff-neutral';
+  headers.push('Pareto');
+  const lines = [
+    `Baseline: ${baseLabel}`,
+    `View: ${state.rosterMetric === 'ops' ? 'Ops/s stats' : 'Latency stats'} + size`,
+    `Ratios: median/size use ×base; Std/P95/P99 use ×med (own median)`,
+    (() => {
+      const s = parseFixtureSelection(state.currentTestData);
+      if (s.kind === 'batch_compound') {
+        return `Scope: compounded batch ${state.currentTestData} · mode ${state.currentMode}`;
+      }
+      if (s.kind === 'all_n') {
+        return `Scope: all data types @ n=${s.n} · mode ${state.currentMode}`;
+      }
+      if (s.kind === 'all_all') {
+        return `Scope: all@all (all types × all n) · mode ${state.currentMode}`;
+      }
+      return `Scope: data type ${state.currentTestData} · mode ${state.currentMode}`;
+    })(),
+    ``,
+    `| ${headers.join(' | ')} |`,
+    `|${headers.map((h, i) => (i === 0 || h === 'Pareto' ? '---' : '---:')).join('|')}|`,
+  ];
+  rows.forEach((r) => {
+    const opt = state.paretoSerializerNames.includes(r.serializer) ? 'yes' : '';
+    const isBaseline = baselineGroup && r.serializer === baselineGroup.serializer;
+    const cells = metricSpecs.map(({ key, higherIsBetter }) => {
+      const cell = formatRosterRelativeCell(
+        r,
+        key,
+        higherIsBetter,
+        scales,
+        baselineGroup,
+        isBaseline
+      );
+      return cell.text;
+    });
+    const name =
+      serializerLabelFromGroup(r) + (isBaseline ? ' (baseline)' : '');
+    lines.push(`| ${name} | ${cells.join(' | ')} | ${opt} |`);
   });
-}
-
-// Table Sorting
-function handleTableSort(key, el) {
-  if (state.sortKey === key) {
-    state.sortDirection = state.sortDirection === 'asc' ? 'desc' : 'asc';
-  } else {
-    state.sortKey = key;
-    state.sortDirection = 'desc';
-  }
-
-  document.querySelectorAll('#analytics-table th').forEach(th => th.className = '');
-  el.className = state.sortDirection === 'asc' ? 'sort-asc' : 'sort-desc';
-
-  saveSettings();
-  renderTable();
-}
-
-function renderTable() {
-  const tbody = document.getElementById('table-body');
-  tbody.innerHTML = '';
-
-  let rows = state.filteredGroups.filter(g => 
-    g.serializer.toLowerCase().includes(state.searchQuery)
-  );
-
-  rows.sort((a, b) => {
-    let valA = a[state.sortKey];
-    let valB = b[state.sortKey];
-
-    if (valA === null || valA === undefined) return 1;
-    if (valB === null || valB === undefined) return -1;
-
-    if (typeof valA === 'string') {
-      return state.sortDirection === 'asc' ? valA.localeCompare(valB) : valB.localeCompare(valA);
-    } else {
-      return state.sortDirection === 'asc' ? valA - valB : valB - valA;
+  copyText(lines.join('\n'), 'Roster Markdown copied');
+}
+
+function copyCompareMarkdown() {
+  const table = document.getElementById('serializer-metrics-table');
+  if (!table) return;
+  const rows = [...table.querySelectorAll('tr')];
+  const md = rows
+    .map((tr) => {
+      const cells = [...tr.children].map((td) => td.textContent.trim().replace(/\|/g, '\\|'));
+      return `| ${cells.join(' | ')} |`;
+    })
+    .filter((line) => !line.includes('Throughput') || line.startsWith('| Metric'));
+  // simpler: all rows
+  const all = rows.map((tr) => {
+    const cells = [...tr.children].map((td) => td.textContent.trim().replace(/\|/g, '\\|'));
+    if (tr.classList.contains('metric-group-row')) {
+      return `\n**${cells[0]}**\n`;
     }
+    return `| ${cells.join(' | ')} |`;
   });
+  copyText(all.join('\n'), 'Compare Markdown copied');
+}
 
-  if (rows.length === 0) {
-    const tr = document.createElement('tr');
-    tr.innerHTML = `<td colspan="7" style="text-align: center; color: var(--text-muted);">No serializers match search query</td>`;
-    tbody.appendChild(tr);
-    return;
+async function copyText(text, okMsg) {
+  try {
+    await navigator.clipboard.writeText(text);
+    showNotification(okMsg || 'Copied', 'success');
+  } catch {
+    showNotification('Clipboard unavailable', 'error');
   }
-
-  rows.forEach(r => {
-    const tr = document.createElement('tr');
-    const isOptimal = state.paretoSerializerNames.includes(r.serializer);
-    
-    tr.innerHTML = `
-      <td><strong>${r.serializer}</strong></td>
-      <td>${formatOps(r.avg_ops_per_sec)}</td>
-      <td>${formatTime(r.avg_time_total_ns)}</td>
-      <td>${formatTime(r.avg_time_ser_ns)}</td>
-      <td>${formatTime(r.avg_time_deser_ns)}</td>
-      <td>${r.median_size_bytes} Bytes</td>
-      <td>
-        ${isOptimal 
-          ? '<span class="badge badge-cyan">Optimal</span>' 
-          : '<span class="badge badge-purple" style="opacity: 0.4;">Compromised</span>'}
-      </td>
-    `;
-    tbody.appendChild(tr);
-  });
 }
 
-// Upload Handler
 function handleFileUpload(file) {
   if (!file) return;
-  
   const status = document.getElementById('upload-status');
-  status.style.display = 'block';
-  status.style.color = 'var(--text-secondary)';
-  status.textContent = `Analyzing ${file.name}...`;
-
+  if (status) {
+    status.style.display = 'block';
+    status.style.color = 'var(--text-secondary)';
+    status.textContent = `Analyzing ${file.name}…`;
+  }
   const reader = new FileReader();
   reader.onload = (e) => {
     try {
@@ -1761,40 +3342,35 @@ function handleFileUpload(file) {
       if (!data.groups || !Array.isArray(data.groups)) {
         throw new Error("Invalid stats format. Missing 'groups' array.");
       }
-      
       processStatsData(data);
-      
-      status.style.color = 'var(--accent-green)';
-      status.textContent = `Successfully loaded ${file.name}!`;
+      if (status) {
+        status.style.color = 'var(--color-green)';
+        status.textContent = `Successfully loaded ${file.name}`;
+      }
       showNotification(`Loaded ${file.name} successfully.`, 'success');
-      
-      document.getElementById('lang-select').value = '';
     } catch (err) {
-      status.style.color = 'var(--accent-red)';
-      status.textContent = `Failed: ${err.message}`;
+      if (status) {
+        status.style.color = 'var(--color-red)';
+        status.textContent = `Failed: ${err.message}`;
+      }
       showNotification(`Upload failed: ${err.message}`, 'error');
     }
   };
-  
   reader.readAsText(file);
 }
 
-// Dynamic CSV parsing and aggregations
 function parseCSV(text) {
-  const lines = text.split('\n').map(line => line.trim()).filter(line => line.length > 0);
-  if (lines.length === 0) return [];
-  
+  const lines = text.trim().split(/\r?\n/);
+  if (lines.length < 2) return [];
   const headers = parseCSVLine(lines[0]);
   const records = [];
-  
   for (let i = 1; i < lines.length; i++) {
+    if (!lines[i].trim()) continue;
     const values = parseCSVLine(lines[i]);
-    if (values.length !== headers.length) continue;
-    
     const rec = {};
-    for (let j = 0; j < headers.length; j++) {
-      rec[headers[j]] = values[j];
-    }
+    headers.forEach((h, idx) => {
+      rec[h] = values[idx];
+    });
     records.push(rec);
   }
   return records;
@@ -1802,95 +3378,94 @@ function parseCSV(text) {
 
 function parseCSVLine(line) {
   const result = [];
-  let current = '';
+  let cur = '';
   let inQuotes = false;
-  
   for (let i = 0; i < line.length; i++) {
-    const char = line[i];
-    if (char === '"') {
-      inQuotes = !inQuotes;
-    } else if (char === ',' && !inQuotes) {
-      result.push(current.trim());
-      current = '';
-    } else {
-      current += char;
-    }
+    const ch = line[i];
+    if (ch === '"') {
+      if (inQuotes && line[i + 1] === '"') {
+        cur += '"';
+        i++;
+      } else inQuotes = !inQuotes;
+    } else if (ch === ',' && !inQuotes) {
+      result.push(cur);
+      cur = '';
+    } else cur += ch;
   }
-  result.push(current.trim());
+  result.push(cur);
   return result;
 }
 
 function aggregateCSVRecords(records) {
-  const groups = {};
-  
-  records.forEach(r => {
-    const serializer = r.SerializerName || r.serializer || '';
-    const testData = r.TestDataName || r.test_data || '';
-    const mode = r.StringOrStream || r.mode || '';
-    
-    if (!serializer || !testData || !mode) return;
-    
-    const key = `${serializer}|${testData}|${mode}`;
-    if (!groups[key]) {
-      groups[key] = {
+  const map = new Map();
+  for (const r of records) {
+    const serializer = r.Serializer || r.serializer;
+    const test_data = r.TestData || r.test_data || r.DataType;
+    const mode = r.Mode || r.mode || 'bytes';
+    if (!serializer) continue;
+    const key = `${serializer}|${test_data}|${mode}`;
+    if (!map.has(key)) {
+      map.set(key, {
         serializer,
-        test_data: testData,
+        test_data,
         mode,
-        timesSer: [],
-        timesDeser: [],
-        timesTotal: [],
+        times: [],
+        ser: [],
+        deser: [],
         sizes: [],
-        opsSec: []
-      };
+        ops: [],
+        fidelities: [],
+      });
     }
-    
-    const tSer = parseFloat(r.TimeSer || r.time_ser || 0);
-    const tDeser = parseFloat(r.TimeDeser || r.time_deser || 0);
-    const tTotal = parseFloat(r.TimeSerAndDeser || r.time_total || 0) || (tSer + tDeser);
-    const size = parseFloat(r.Size || r.size || 0);
-    const ops = parseFloat(r.OpPerSecSerAndDeser || r.ops_sec || 0);
-    
-    groups[key].timesSer.push(tSer);
-    groups[key].timesDeser.push(tDeser);
-    groups[key].timesTotal.push(tTotal);
-    groups[key].sizes.push(size);
-    groups[key].opsSec.push(ops);
-  });
-  
-  const resultGroups = [];
-  Object.values(groups).forEach(g => {
-    const avgTotal = mean(g.timesTotal);
-    const avgOps = mean(g.opsSec) || (1e9 / avgTotal);
-    
-    resultGroups.push({
+    const g = map.get(key);
+    const total = Number(r.TotalTimeNs || r.total_time_ns || r.TimeNs);
+    const ser = Number(r.SerTimeNs || r.ser_time_ns);
+    const deser = Number(r.DeserTimeNs || r.deser_time_ns);
+    const size = Number(r.SizeBytes || r.size_bytes || r.PayloadSize);
+    const ops = Number(r.OpsPerSec || r.ops_per_sec);
+    const fid = Number(r.FidelityScore || r.fidelity);
+    if (Number.isFinite(total)) g.times.push(total);
+    if (Number.isFinite(ser)) g.ser.push(ser);
+    if (Number.isFinite(deser)) g.deser.push(deser);
+    if (Number.isFinite(size)) g.sizes.push(size);
+    if (Number.isFinite(ops)) g.ops.push(ops);
+    if (Number.isFinite(fid)) g.fidelities.push(fid);
+  }
+
+  const groups = [];
+  for (const g of map.values()) {
+    if (!g.times.length && !g.ops.length) continue;
+    const avg_time_total_ns = mean(g.times);
+    const avg_ops_per_sec =
+      g.ops.length > 0 ? mean(g.ops) : avg_time_total_ns > 0 ? 1e9 / avg_time_total_ns : 0;
+    groups.push({
       serializer: g.serializer,
       test_data: g.test_data,
       mode: g.mode,
-      avg_time_ser_ns: mean(g.timesSer),
-      avg_time_deser_ns: mean(g.timesDeser),
-      avg_time_total_ns: avgTotal,
+      avg_time_total_ns,
+      avg_time_ser_ns: mean(g.ser),
+      avg_time_deser_ns: mean(g.deser),
+      avg_ops_per_sec,
       median_size_bytes: median(g.sizes),
-      avg_ops_per_sec: avgOps,
-      runs: g.timesTotal.length
+      mean_fidelity: g.fidelities.length ? mean(g.fidelities) : null,
+      runs: Math.max(g.times.length, g.ops.length),
     });
-  });
-  
-  return resultGroups;
+  }
+  return groups;
 }
 
 function mean(arr) {
-  if (arr.length === 0) return 0;
-  return arr.reduce((sum, val) => sum + val, 0) / arr.length;
+  if (!arr || !arr.length) return null;
+  return arr.reduce((a, b) => a + b, 0) / arr.length;
 }
 
 function median(arr) {
-  if (arr.length === 0) return 0;
-  const sorted = [...arr].sort((a, b) => a - b);
-  const mid = Math.floor(sorted.length / 2);
-  return sorted.length % 2 !== 0 ? sorted[mid] : (sorted[mid - 1] + sorted[mid]) / 2;
+  if (!arr || !arr.length) return null;
+  const s = [...arr].sort((a, b) => a - b);
+  const m = Math.floor(s.length / 2);
+  return s.length % 2 ? s[m] : (s[m - 1] + s[m]) / 2;
 }
 
-// Download helpers
 function triggerDownload(url, filename) {
   const a = document.createElement('a');
   a.href = url;
@@ -1900,73 +3475,48 @@ function triggerDownload(url, filename) {
   a.remove();
 }
 
+function downloadDataUrl(dataUrl, filename) {
+  const a = document.createElement('a');
+  a.href = dataUrl;
+  a.download = filename;
+  document.body.appendChild(a);
+  a.click();
+  a.remove();
+}
+
 async function downloadFileWithFallback(url, fallbackUrl, filename) {
   try {
-    const res = await fetch(url);
-    if (res.ok) {
-      triggerDownload(url, filename);
-    } else if (fallbackUrl) {
-      const fbRes = await fetch(fallbackUrl);
-      if (fbRes.ok) {
-        // Change suffix to environment json
-        const fbFilename = filename.replace('.configs.json', '.environment.json');
-        triggerDownload(fallbackUrl, fbFilename);
-      } else {
-        showNotification("File not found on local server.", "error");
-      }
-    } else {
-      showNotification("File not found on local server.", "error");
-    }
+    let res = await fetch(url);
+    if (!res.ok && fallbackUrl) res = await fetch(fallbackUrl);
+    if (!res.ok) throw new Error('Download failed');
+    const blob = await res.blob();
+    const obj = URL.createObjectURL(blob);
+    triggerDownload(obj, filename);
+    URL.revokeObjectURL(obj);
   } catch (e) {
-    showNotification("Download failed: " + e.message, "error");
+    showNotification('Download failed: ' + e.message, 'error');
   }
 }
 
-// Helpers
-function formatTime(ns) {
-  if (ns === null || ns === undefined) return '-';
-  if (ns < 1000) return `${ns.toFixed(0)}ns`;
-  if (ns < 1000000) return `${(ns / 1000).toFixed(2)}µs`;
-  return `${(ns / 1000000).toFixed(2)}ms`;
-}
-
-function formatOps(ops) {
-  if (ops === null || ops === undefined) return '-';
-  if (ops < 1000) return `${ops.toFixed(0)}/s`;
-  if (ops < 1000000) return `${(ops / 1000).toFixed(1)}K/s`;
-  return `${(ops / 1000000).toFixed(2)}M/s`;
-}
-
 function showNotification(msg, type) {
   const notif = document.createElement('div');
   notif.style.position = 'fixed';
   notif.style.bottom = '2rem';
   notif.style.right = '2rem';
-  notif.style.padding = '1rem 1.5rem';
+  notif.style.padding = '0.85rem 1.25rem';
   notif.style.borderRadius = '8px';
   notif.style.color = '#fff';
   notif.style.zIndex = '10000';
-  notif.style.backdropFilter = 'blur(10px)';
-  notif.style.boxShadow = '0 10px 30px rgba(0,0,0,0.5)';
-  notif.style.fontSize = '0.95rem';
-  notif.style.transition = 'opacity 0.3s ease';
-  
-  if (type === 'error') {
-    notif.style.background = 'rgba(239, 68, 68, 0.8)';
-    notif.style.border = '1px solid rgba(239, 68, 68, 0.3)';
-  } else if (type === 'info') {
-    notif.style.background = 'rgba(59, 130, 246, 0.8)';
-    notif.style.border = '1px solid rgba(59, 130, 246, 0.3)';
-  } else {
-    notif.style.background = 'rgba(16, 185, 129, 0.8)';
-    notif.style.border = '1px solid rgba(16, 185, 129, 0.3)';
-  }
-  
+  notif.style.fontSize = '0.9rem';
+  notif.style.boxShadow = '0 8px 24px rgba(0,0,0,0.2)';
   notif.textContent = msg;
+  if (type === 'error') notif.style.background = 'rgba(217, 48, 37, 0.92)';
+  else if (type === 'info') notif.style.background = 'rgba(26, 115, 232, 0.92)';
+  else notif.style.background = 'rgba(30, 142, 62, 0.92)';
   document.body.appendChild(notif);
-  
   setTimeout(() => {
     notif.style.opacity = '0';
+    notif.style.transition = 'opacity 0.3s';
     setTimeout(() => notif.remove(), 300);
-  }, 4000);
+  }, 2800);
 }
diff --git a/dashboard/package.json b/dashboard/package.json
index 9a1831fd..4ad4d39e 100644
--- a/dashboard/package.json
+++ b/dashboard/package.json
@@ -1,6 +1,6 @@
 {
   "name": "serializer-benchmark-dashboard",
-  "version": "0.2.0",
+  "version": "0.3.0",
   "description": "Interactive analytics dashboard for serializer benchmarks",
   "scripts": {
     "dev": "vite --port 5173 --open",
@@ -10,5 +10,6 @@
   },
   "devDependencies": {
     "vite": "^5.0.0"
-  }
+  },
+  "type": "module"
 }
diff --git a/dashboard/public/data/c_latest.json.gz b/dashboard/public/data/c_latest.json.gz
index e2944698..ffc8032c 100644
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diff --git a/dashboard/public/data/cpp_latest.json.gz b/dashboard/public/data/cpp_latest.json.gz
index a89a8387..51a4a176 100644
Binary files a/dashboard/public/data/cpp_latest.json.gz and b/dashboard/public/data/cpp_latest.json.gz differ
diff --git a/dashboard/public/data/csharp_latest.json.gz b/dashboard/public/data/csharp_latest.json.gz
index 2587640c..0bff5975 100644
Binary files a/dashboard/public/data/csharp_latest.json.gz and b/dashboard/public/data/csharp_latest.json.gz differ
diff --git a/dashboard/public/data/go_latest.json.gz b/dashboard/public/data/go_latest.json.gz
index b06c0cec..e60196e5 100644
Binary files a/dashboard/public/data/go_latest.json.gz and b/dashboard/public/data/go_latest.json.gz differ
diff --git a/dashboard/public/data/java_latest.json.gz b/dashboard/public/data/java_latest.json.gz
index 8624dfae..ed0b4449 100644
Binary files a/dashboard/public/data/java_latest.json.gz and b/dashboard/public/data/java_latest.json.gz differ
diff --git a/dashboard/public/data/javascript_latest.json.gz b/dashboard/public/data/javascript_latest.json.gz
index 393ccaf7..d91232e9 100644
Binary files a/dashboard/public/data/javascript_latest.json.gz and b/dashboard/public/data/javascript_latest.json.gz differ
diff --git a/dashboard/public/data/python_latest.json.gz b/dashboard/public/data/python_latest.json.gz
index bc91411b..c21faab7 100644
Binary files a/dashboard/public/data/python_latest.json.gz and b/dashboard/public/data/python_latest.json.gz differ
diff --git a/dashboard/public/data/rust_latest.json.gz b/dashboard/public/data/rust_latest.json.gz
index 4d2559e8..268ab954 100644
Binary files a/dashboard/public/data/rust_latest.json.gz and b/dashboard/public/data/rust_latest.json.gz differ
diff --git a/dashboard/public/data/stats_c_latest.json b/dashboard/public/data/stats_c_latest.json
deleted file mode 100644
index e3c7cd8e..00000000
--- a/dashboard/public/data/stats_c_latest.json
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
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diff --git a/dashboard/public/data/stats_csharp_latest.json.gz b/dashboard/public/data/stats_csharp_latest.json.gz
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--- a/dashboard/public/data/stats_go_latest.json
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@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/dashboard/public/data/stats_go_latest.json.gz b/dashboard/public/data/stats_go_latest.json.gz
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diff --git a/dashboard/public/data/stats_java_latest.json b/dashboard/public/data/stats_java_latest.json
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index 4dfb95b4..00000000
--- a/dashboard/public/data/stats_java_latest.json
+++ /dev/null
@@ -1 +0,0 @@
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diff --git a/dashboard/public/data/stats_rust_latest.json.gz b/dashboard/public/data/stats_rust_latest.json.gz
new file mode 100644
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diff --git a/dashboard/public/data/stats_swift_latest.json b/dashboard/public/data/stats_swift_latest.json
deleted file mode 100644
index 97cb4c16..00000000
--- a/dashboard/public/data/stats_swift_latest.json
+++ /dev/null
@@ -1 +0,0 @@
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"deser_mean_ns": 1489188.456521739, "deser_median_ns": 1479520.0, "deser_std_ns": 54084.879322688124, "deser_mad_ns": 33878.0, "deser_cv": 0.03631835788534975, "deser_min_ns": 1417934.0, "deser_max_ns": 1631794.0, "deser_p5_ns": 1425549.35, "deser_p25_ns": 1448124.75, "deser_p50_ns": 1479520.0, "deser_p75_ns": 1516929.5, "deser_p95_ns": 1594519.5, "deser_p99_ns": 1626453.21, "deser_ci_low_ns": 1478502.8633152174, "deser_ci_high_ns": 1499985.6861413042, "total_mean_ns": 10831885.97826087, "total_median_ns": 10798609.5, "total_std_ns": 148922.87231049608, "total_mad_ns": 72130.5, "total_cv": 0.013748563510489115, "total_min_ns": 10551427.0, "total_max_ns": 11213783.0, "total_p5_ns": 10655621.15, "total_p25_ns": 10737113.25, "total_p50_ns": 10798609.5, "total_p75_ns": 10894568.5, "total_p95_ns": 11119489.9, "total_p99_ns": 11161583.58, "total_ci_low_ns": 10802459.146467391, "total_ci_high_ns": 10864351.636141306, "mean_fidelity": 1.0, "mean_memory_peak_bytes": 0.0, "StreamMode": "adapted", "fastest_in_group": "SwiftProtobuf", "effect_vs_fastest_cliffs_delta": 1.0, "effect_vs_fastest_cliffs_label": "large", "effect_vs_fastest_hedges_g": 89.76934116181}, {"serializer": "Foundation.PropertyListEncoder", "test_data": "event", "type_config_hash": "963dc8e1b85e", "data_type_instance_count": 100, "mode": "stream", "language": "swift", "serializer_version": "Foundation", "avg_time_ser_ns": 2558054.2608695654, "avg_time_deser_ns": 1900882.5217391304, "avg_time_total_ns": 4458936.782608695, "median_size_bytes": 21061.0, "avg_ops_per_sec": 224.26870995353096, "min_ops_per_sec": 218.18231008375363, "max_ops_per_sec": 230.14096364164013, "runs": 92, "runs_raw": 100, "warmup_skipped": 1, "outliers_removed": 7, "ser_mean_ns": 2558054.2608695654, "ser_median_ns": 2551642.0, "ser_std_ns": 37884.957550333085, "ser_mad_ns": 21305.0, "ser_cv": 0.014810067999673613, "ser_min_ns": 2479548.0, "ser_max_ns": 2642714.0, "ser_p5_ns": 2494972.35, "ser_p25_ns": 2534248.5, "ser_p50_ns": 2551642.0, "ser_p75_ns": 2586532.25, "ser_p95_ns": 2624682.7, "ser_p99_ns": 2641403.6, "ser_ci_low_ns": 2550553.9008152173, "ser_ci_high_ns": 2565476.868478261, "deser_mean_ns": 1900882.5217391304, "deser_median_ns": 1898818.0, "deser_std_ns": 24090.548305484102, "deser_mad_ns": 16718.5, "deser_cv": 0.012673349367978561, "deser_min_ns": 1844534.0, "deser_max_ns": 1959355.0, "deser_p5_ns": 1866092.7, "deser_p25_ns": 1882316.75, "deser_p50_ns": 1898818.0, "deser_p75_ns": 1915894.25, "deser_p95_ns": 1939617.1, "deser_p99_ns": 1953880.44, "deser_ci_low_ns": 1896046.9027173913, "deser_ci_high_ns": 1905840.9529891303, "total_mean_ns": 4458936.782608695, "total_median_ns": 4447788.0, "total_std_ns": 53165.83260712997, "total_mad_ns": 31547.5, "total_cv": 0.01192343269240641, "total_min_ns": 4345163.0, "total_max_ns": 4583323.0, "total_p5_ns": 4370136.15, "total_p25_ns": 4425430.0, "total_p50_ns": 4447788.0, "total_p75_ns": 4496816.0, "total_p95_ns": 4557573.7, "total_p99_ns": 4582235.55, "total_ci_low_ns": 4448547.707336956, "total_ci_high_ns": 4469960.406793478, "mean_fidelity": 1.0, "mean_memory_peak_bytes": 0.0, "StreamMode": "adapted", "fastest_in_group": "SwiftProtobuf", "effect_vs_fastest_cliffs_delta": 1.0, "effect_vs_fastest_cliffs_label": "large", "effect_vs_fastest_hedges_g": 82.40439851684074}, {"serializer": "Yams", "test_data": "event", "type_config_hash": "963dc8e1b85e", "data_type_instance_count": 100, "mode": "stream", "language": "swift", "serializer_version": "5.4.0", "avg_time_ser_ns": 12609435.11235955, "avg_time_deser_ns": 5690150.303370787, "avg_time_total_ns": 18299585.41573034, "median_size_bytes": 25245.0, "avg_ops_per_sec": 54.64604674269829, "min_ops_per_sec": 53.340149493236574, "max_ops_per_sec": 55.53682730323719, "runs": 89, "runs_raw": 100, "warmup_skipped": 1, "outliers_removed": 10, "ser_mean_ns": 12609435.11235955, "ser_median_ns": 12576992.0, "ser_std_ns": 124007.84594665025, "ser_mad_ns": 81096.0, "ser_cv": 0.00983452825932701, "ser_min_ns": 12436766.0, "ser_max_ns": 12999566.0, "ser_p5_ns": 12468456.2, "ser_p25_ns": 12517398.0, "ser_p50_ns": 12576992.0, "ser_p75_ns": 12687819.0, "ser_p95_ns": 12818793.2, "ser_p99_ns": 12979293.44, "ser_ci_low_ns": 12583596.729213482, "ser_ci_high_ns": 12635011.003370788, "deser_mean_ns": 5690150.303370787, "deser_median_ns": 5672326.0, "deser_std_ns": 76124.7605921604, "deser_mad_ns": 50377.0, "deser_cv": 0.013378339153372604, "deser_min_ns": 5565776.0, "deser_max_ns": 5920050.0, "deser_p5_ns": 5593663.6, "deser_p25_ns": 5634790.0, "deser_p50_ns": 5672326.0, "deser_p75_ns": 5733801.0, "deser_p95_ns": 5845139.8, "deser_p99_ns": 5879083.36, "deser_ci_low_ns": 5675063.633426966, "deser_ci_high_ns": 5705282.358707866, "total_mean_ns": 18299585.41573034, "total_median_ns": 18266126.0, "total_std_ns": 169319.1534631358, "total_mad_ns": 121940.0, "total_cv": 0.009252622374580624, "total_min_ns": 18006070.0, "total_max_ns": 18747604.0, "total_p5_ns": 18077432.6, "total_p25_ns": 18179752.0, "total_p50_ns": 18266126.0, "total_p75_ns": 18416493.0, "total_p95_ns": 18613844.6, "total_p99_ns": 18719900.72, "total_ci_low_ns": 18263755.60477528, "total_ci_high_ns": 18334825.099719103, "mean_fidelity": 1.0, "mean_memory_peak_bytes": 0.0, "StreamMode": "adapted", "fastest_in_group": "SwiftProtobuf", "effect_vs_fastest_cliffs_delta": 1.0, "effect_vs_fastest_cliffs_label": "large", "effect_vs_fastest_hedges_g": 140.6730488261324}, {"serializer": "SwiftAvroCore", "test_data": "event", "type_config_hash": "963dc8e1b85e", "data_type_instance_count": 100, "mode": "stream", "language": "swift", "serializer_version": "2.3.0", "avg_time_ser_ns": 4552571.808988764, "avg_time_deser_ns": 985248.6404494382, "avg_time_total_ns": 5537820.449438202, "median_size_bytes": 10448.0, "avg_ops_per_sec": 180.5764576750493, "min_ops_per_sec": 175.34231202865794, "max_ops_per_sec": 183.95595064388263, "runs": 89, "runs_raw": 100, "warmup_skipped": 1, "outliers_removed": 10, "ser_mean_ns": 4552571.808988764, "ser_median_ns": 4541496.0, "ser_std_ns": 49557.569253499234, "ser_mad_ns": 25249.0, "ser_cv": 0.010885620553123613, "ser_min_ns": 4450122.0, "ser_max_ns": 4680950.0, "ser_p5_ns": 4487479.0, "ser_p25_ns": 4521890.0, "ser_p50_ns": 4541496.0, "ser_p75_ns": 4572741.0, "ser_p95_ns": 4656390.2, "ser_p99_ns": 4668198.8, "ser_ci_low_ns": 4543138.338483145, "ser_ci_high_ns": 4562545.677247191, "deser_mean_ns": 985248.6404494382, "deser_median_ns": 983137.0, "deser_std_ns": 19876.193051811773, "deser_mad_ns": 14148.0, "deser_cv": 0.02017378378999326, "deser_min_ns": 953931.0, "deser_max_ns": 1036670.0, "deser_p5_ns": 960955.2, "deser_p25_ns": 969618.0, "deser_p50_ns": 983137.0, "deser_p75_ns": 997285.0, "deser_p95_ns": 1021288.2, "deser_p99_ns": 1028761.4400000001, "deser_ci_low_ns": 981382.7556179775, "deser_ci_high_ns": 989646.8491573033, "total_mean_ns": 5537820.449438202, "total_median_ns": 5529748.0, "total_std_ns": 58345.07088435368, "total_mad_ns": 32046.0, "total_cv": 0.010535746223096243, "total_min_ns": 5436084.0, "total_max_ns": 5703130.0, "total_p5_ns": 5458990.2, "total_p25_ns": 5496826.0, "total_p50_ns": 5529748.0, "total_p75_ns": 5560201.0, "total_p95_ns": 5651137.0, "total_p99_ns": 5693623.36, "total_ci_low_ns": 5526367.431179775, "total_ci_high_ns": 5550111.496348315, "mean_fidelity": 1.0, "mean_memory_peak_bytes": 0.0, "StreamMode": "adapted", "fastest_in_group": "SwiftProtobuf", "effect_vs_fastest_cliffs_delta": 1.0, "effect_vs_fastest_cliffs_label": "large", "effect_vs_fastest_hedges_g": 100.63812337566743}, {"serializer": "SwiftMsgpack", "test_data": "event", "type_config_hash": "963dc8e1b85e", "data_type_instance_count": 100, "mode": "stream", "language": "swift", "serializer_version": "1.2.1", "avg_time_ser_ns": 2786859.989361702, "avg_time_deser_ns": 1137120.670212766, "avg_time_total_ns": 3923980.659574468, "median_size_bytes": 19848.0, "avg_ops_per_sec": 254.84325402063627, "min_ops_per_sec": 243.02145660742534, "max_ops_per_sec": 263.6705257484815, "runs": 94, "runs_raw": 100, "warmup_skipped": 1, "outliers_removed": 5, "ser_mean_ns": 2786859.989361702, "ser_median_ns": 2779812.0, "ser_std_ns": 50579.70569489982, "ser_mad_ns": 34285.0, "ser_cv": 0.018149352995119255, "ser_min_ns": 2701427.0, "ser_max_ns": 2911837.0, "ser_p5_ns": 2719819.45, "ser_p25_ns": 2749420.75, "ser_p50_ns": 2779812.0, "ser_p75_ns": 2817584.75, "ser_p95_ns": 2884939.15, "ser_p99_ns": 2910398.29, "ser_ci_low_ns": 2777739.500531915, "ser_ci_high_ns": 2797372.6800531917, "deser_mean_ns": 1137120.670212766, "deser_median_ns": 1135441.0, "deser_std_ns": 24867.199550225116, "deser_mad_ns": 17825.5, "deser_cv": 0.021868566988209114, "deser_min_ns": 1074738.0, "deser_max_ns": 1204573.0, "deser_p5_ns": 1102555.05, "deser_p25_ns": 1117617.0, "deser_p50_ns": 1135441.0, "deser_p75_ns": 1152513.75, "deser_p95_ns": 1181412.8, "deser_p99_ns": 1187211.7599999998, "deser_ci_low_ns": 1132104.7962765957, "deser_ci_high_ns": 1142067.7734042553, "total_mean_ns": 3923980.659574468, "total_median_ns": 3917063.5, "total_std_ns": 67027.00899365533, "total_mad_ns": 43242.5, "total_cv": 0.017081381079213576, "total_min_ns": 3792612.0, "total_max_ns": 4114863.0, "total_p5_ns": 3827962.15, "total_p25_ns": 3874232.75, "total_p50_ns": 3917063.5, "total_p75_ns": 3960701.5, "total_p95_ns": 4052612.1, "total_p99_ns": 4092275.1599999997, "total_ci_low_ns": 3910553.8662234046, "total_ci_high_ns": 3936611.388297872, "mean_fidelity": 1.0, "mean_memory_peak_bytes": 0.0, "StreamMode": "adapted", "fastest_in_group": "SwiftProtobuf", "effect_vs_fastest_cliffs_delta": 1.0, "effect_vs_fastest_cliffs_label": "large", "effect_vs_fastest_hedges_g": 56.2091175569665}], "pareto_front": [{"serializer": "SwiftAvroCore", "test_data": "message", "mode": "bytes", "time": 46619.22619047619, "size": 44.0}, {"serializer": "SwiftProtobuf", "test_data": "message", "mode": "bytes", "time": 3355.215909090909, "size": 50.0}, {"serializer": "SwiftProtobuf", "test_data": "message", "mode": "stream", "time": 9543.511111111111, "size": 50.0}, {"serializer": "SwiftAvroCore", "test_data": "message", "mode": "stream", "time": 53740.96703296703, "size": 44.0}, {"serializer": "SwiftProtobuf", "test_data": "document", "mode": "bytes", "time": 8767.342105263158, "size": 155.0}, {"serializer": "SwiftAvroCore", "test_data": "document", "mode": "bytes", "time": 135647.93023255814, "size": 114.0}, {"serializer": "FlatBuffers", "test_data": "document", "mode": "bytes", "time": 7603.273972602739, "size": 440.0}, {"serializer": "SwiftAvroCore", "test_data": "document", "mode": "stream", "time": 149144.6590909091, "size": 114.0}, {"serializer": "SwiftProtobuf", "test_data": "document", "mode": "stream", "time": 22926.345679012345, "size": 155.0}, {"serializer": "SwiftProtobuf", "test_data": "telemetry", "mode": "bytes", "time": 4161.939759036145, "size": 291.0}, {"serializer": "SwiftAvroCore", "test_data": "telemetry", "mode": "bytes", "time": 56433.03571428572, "size": 288.0}, {"serializer": "SwiftAvroCore", "test_data": "telemetry", "mode": "stream", "time": 79285.93902439025, "size": 288.0}, {"serializer": "SwiftProtobuf", "test_data": "telemetry", "mode": "stream", "time": 26433.703703703704, "size": 291.0}, {"serializer": "BinaryCodable", "test_data": "strings", "mode": "bytes", "time": 36637.39024390244, "size": 344.0}, {"serializer": "SwiftAvroCore", "test_data": "strings", "mode": "bytes", "time": 44240.77380952381, "size": 338.0}, {"serializer": "SwiftProtobuf", "test_data": "strings", "mode": "bytes", "time": 5101.471264367816, "size": 368.0}, {"serializer": "BinaryCodable", "test_data": "strings", "mode": "stream", "time": 61252.03846153846, "size": 344.0}, {"serializer": "SwiftAvroCore", "test_data": "strings", "mode": "stream", "time": 69811.21176470588, "size": 338.0}, {"serializer": "SwiftProtobuf", "test_data": "strings", "mode": "stream", "time": 32178.41176470588, "size": 368.0}, {"serializer": "SwiftAvroCore", "test_data": "event", "mode": "bytes", "time": 79232.13793103448, "size": 105.0}, {"serializer": "SwiftProtobuf", "test_data": "event", "mode": "bytes", "time": 6921.1973684210525, "size": 123.0}, {"serializer": "SwiftAvroCore", "test_data": "event", "mode": "stream", "time": 91979.74074074074, "size": 105.0}, {"serializer": "SwiftProtobuf", "test_data": "event", "mode": "stream", "time": 18240.831325301206, "size": 123.0}]}
\ No newline at end of file
diff --git a/dashboard/public/data/stats_swift_latest.json.gz b/dashboard/public/data/stats_swift_latest.json.gz
new file mode 100644
index 00000000..69bdfabf
Binary files /dev/null and b/dashboard/public/data/stats_swift_latest.json.gz differ
diff --git a/dashboard/public/data/swift_latest.json.gz b/dashboard/public/data/swift_latest.json.gz
index d3c90968..e844d4fc 100644
Binary files a/dashboard/public/data/swift_latest.json.gz and b/dashboard/public/data/swift_latest.json.gz differ
diff --git a/dashboard/scripts/sync-data.py b/dashboard/scripts/sync-data.py
index f47c06fa..48c6991e 100644
--- a/dashboard/scripts/sync-data.py
+++ b/dashboard/scripts/sync-data.py
@@ -102,26 +102,42 @@ def main():
             except Exception as e:
                 print(f"Error loading stats JSON: {e}")
 
-        # Plain stats JSON for cross-lang fetch (must stay in sync with reports/)
+        # Multi-policy stats as gzip only (schema 2.2; recommendation A).
+        # Dashboard prefers stats_<lang>_latest.json.gz over plain JSON.
         dest_stats_path = os.path.join(target_data_dir, f"stats_{lang}_latest.json")
+        dest_stats_gz_path = os.path.join(target_data_dir, f"stats_{lang}_latest.json.gz")
         if stats_data:
-            print(f"Copying stats JSON to: {dest_stats_path}")
-            with open(dest_stats_path, "w", encoding="utf-8") as f:
-                json.dump(stats_data, f, indent=None)
-        elif os.path.exists(dest_stats_path):
-            # Drop outdated stats when reports has no file for this language
-            print(f"Removing stale stats file: {dest_stats_path}")
-            os.remove(dest_stats_path)
-
-        # Assemble compact payload
+            stats_bytes = json.dumps(stats_data, indent=None, separators=(",", ":")).encode(
+                "utf-8"
+            )
+            print(f"Writing gzipped stats to: {dest_stats_gz_path} ({len(stats_bytes)} raw bytes)")
+            with gzip.open(dest_stats_gz_path, "wb", compresslevel=9) as f:
+                f.write(stats_bytes)
+            # Remove plain JSON if present (avoid double storage in git)
+            if os.path.exists(dest_stats_path):
+                print(f"Removing plain stats file: {dest_stats_path}")
+                os.remove(dest_stats_path)
+        else:
+            for p in (dest_stats_path, dest_stats_gz_path):
+                if os.path.exists(p):
+                    print(f"Removing stale stats file: {p}")
+                    os.remove(p)
+
+        # Assemble compact payload.
+        # Omit full CSV by default (multi-MB); set DASHBOARD_INCLUDE_CSV=1 to embed.
+        include_csv = os.environ.get("DASHBOARD_INCLUDE_CSV", "").strip() in ("1", "true", "yes")
         payload = {
             "language": lang,
             "run_id": latest_run,
             "stats": stats_data,
             "configs": configs_data,
             "errors": errors_data,
-            "csv_data": csv_data
         }
+        if include_csv:
+            payload["csv_data"] = csv_data
+        elif csv_data:
+            payload["csv_omitted"] = True
+            payload["csv_bytes"] = len(csv_data.encode("utf-8"))
 
         # Write as gzip-compressed JSON
         dest_gzip_path = os.path.join(target_data_dir, f"{lang}_latest.json.gz")
diff --git a/dashboard/vite.config.js b/dashboard/vite.config.js
index e8654146..b0f62491 100644
--- a/dashboard/vite.config.js
+++ b/dashboard/vite.config.js
@@ -1,9 +1,33 @@
 import { defineConfig } from 'vite';
+import { existsSync, readdirSync, unlinkSync } from 'fs';
+import { resolve, join } from 'path';
+import { fileURLToPath } from 'url';
+
+const __dirname = fileURLToPath(new URL('.', import.meta.url));
+
+/** Remove prior hashed assets so docs/dashboard/assets does not accumulate orphans. */
+function cleanDashboardAssets() {
+  return {
+    name: 'clean-dashboard-assets',
+    buildStart() {
+      const assetsDir = resolve(__dirname, '../docs/dashboard/assets');
+      if (!existsSync(assetsDir)) return;
+      for (const f of readdirSync(assetsDir)) {
+        try {
+          unlinkSync(join(assetsDir, f));
+        } catch (_) {
+          /* ignore */
+        }
+      }
+    },
+  };
+}
 
 export default defineConfig({
   base: './',
+  plugins: [cleanDashboardAssets()],
   build: {
     outDir: '../docs/dashboard',
-    emptyOutDir: false
-  }
+    emptyOutDir: false,
+  },
 });
diff --git a/docs/analysis/ANALYSIS_METHODOLOGY.md b/docs/analysis/ANALYSIS_METHODOLOGY.md
index d174cc07..8024f474 100644
--- a/docs/analysis/ANALYSIS_METHODOLOGY.md
+++ b/docs/analysis/ANALYSIS_METHODOLOGY.md
@@ -114,6 +114,29 @@ Default method: **[John Tukey](https://en.wikipedia.org/wiki/John_Tukey "John Tu
 
 Removed count: `outliers_removed`. Final `runs` is the same for serialize, deserialize, and total. IQR mainly stabilizes the **mean** against rare stalls; always look at dispersion and [confidence intervals](https://en.wikipedia.org/wiki/Confidence_interval "Confidence interval — range of plausible values for a parameter")<img src="https://en.wikipedia.org/static/images/icons/wikipedia.png" alt="" width="14" height="14" style="vertical-align: text-bottom; margin-left: 0.15em;" /> too.
 
+### Dashboard filter policies (multi-aggregation export)
+
+Machine-readable `stats_<lang>_latest.json` (schema **2.2**, published as **`.json.gz`**) recomputes every group under **four fixed sample policies** so the dashboard can research outliers without re-running filters in the browser:
+
+| Policy id | Behavior |
+|-----------|----------|
+| `all` | Post-warmup only; no drop, no winsorize |
+| `iqr_1.5` | Paired IQR with **k = 1.5** (canonical / default rankings) |
+| `iqr_3` | Paired IQR with **k = 3** (looser fences) |
+| `winsorize_5_95` | Clip each series at the 5th/95th percentile; **n** unchanged (`values_clipped` counts affected rows) |
+
+Export fields (compact):
+
+- `default_filter_policy` — usually `iqr_1.5`
+- `filter_policies` — catalog once (label, description, method, k, …)
+- `groups[]` — identity fields once + `variants.<policy>` metrics (no duplicated flat lists)
+- per-variant `filter` — counts / fences / method only (labels live in the catalog)
+- Pareto is **not** precomputed; the dashboard recalculates from the active policy metrics
+
+Published dashboard path: `dashboard/public/data/stats_<lang>_latest.json.gz` (gzip of the same JSON).
+
+Markdown language pages still use the configured single `statistics.outlier_method` path (default IQR 1.5). The multi-policy pack is for the interactive dashboard **Samples** control.
+
 ### Descriptive statistics (per group)
 
 | Kind | What we report |
diff --git a/docs/analysis/METRICS.md b/docs/analysis/METRICS.md
index 29be8004..05c552c5 100644
--- a/docs/analysis/METRICS.md
+++ b/docs/analysis/METRICS.md
@@ -75,6 +75,8 @@ After warmup drop and optional outlier filter, analysis groups rows by:
 | `total_ci_low_ns` / `total_ci_high_ns` | [Bootstrap](https://en.wikipedia.org/wiki/Bootstrapping_(statistics) "Bootstrapping (statistics)") [confidence interval](https://en.wikipedia.org/wiki/Confidence_interval "Confidence interval") on **mean** total | medium | — |
 | `avg_ops_per_sec` | `1e9 / total_mean_ns` | high (display) | **yes** |
 | `runs` / `runs_raw` / `warmup_skipped` / `outliers_removed` | Sample provenance | high | — |
+| `values_clipped` | Rows touched by winsorize (0 for drop filters) | medium | — |
+| `filter` | Policy provenance block (`policy`, `method`, `iqr_k`, fences, counts) | high (dashboard) | — |
 
 **Tip:** lower time is better; higher ops/s is better. Medians resist wild spikes better than means; means still matter for throughput.