From 3cfb95bf242ede5911769bbbda68a21bd0b37ffa Mon Sep 17 00:00:00 2001
From: Jammy2211 <JNightingale2211@gmail.com>
Date: Wed, 7 Oct 2026 09:06:13 +0100
Subject: [PATCH] fix: expose Pulse profiling measurements and related hazards

---
 REFERENCE.md                             |  33 ++-
 dashboard.html                           | 352 ++++++++++++++++++++---
 pulse/setup_browser.css                  |  29 ++
 pulse/setup_browser.js                   | 323 ++++++++++++++++++---
 tests/browser_fixture.py                 |  39 +++
 tests/browser_setup.cjs                  | 246 +++++++++++++++-
 tests/fixtures/browser_measurements.json |   1 +
 tests/test_setup_browser.py              |  20 ++
 8 files changed, 966 insertions(+), 77 deletions(-)
 create mode 100644 tests/fixtures/browser_measurements.json

diff --git a/REFERENCE.md b/REFERENCE.md
index c2fbc5e..c40d623 100644
--- a/REFERENCE.md
+++ b/REFERENCE.md
@@ -109,8 +109,7 @@ IDs are non-empty and unique within each list; references resolve within the
 same document and project. `comparisons` must be `[]`: this catalogue presents
 selected results, not release trends. Keep `comparison_policy.id` explicitly
 labelled, e.g. `no-temporal-comparisons`, for common receipt/board compatibility.
-The existing board can ingest/render v2 metadata; the interactive setup browser
-is a subsequent phase. Historical v1 feeds and their comparison rules remain
+The board provides an interactive setup browser over captured v2 evidence. Historical v1 feeds and their comparison rules remain
 supported without rewriting measurements, pins, or policy.
 
 ### Setups
@@ -290,3 +289,33 @@ candidate's evidence at the captured commit.
   Main writers share the concurrency group `pulse-main-writers`.
 - `pages_dashboard.yml` — publishes `dashboard.html` as `index.html` with `badge.json`
   and `state.json`, after validating the feed with `PyAutoBrain/board/_state.py`.
+
+
+### Browsing measurement availability
+
+The setup browser lists runtime, breakdown, compilation and memory availability
+per model/instrument, then selects one exact evidence run. Runtime evidence is
+the deterministic default when available; exact run links open a populated axis
+without substituting a different setup. Selecting a device narrows recorded runs,
+and a compatible filter persists when changing runs. Counts describe availability,
+not scientific comparability or acceptance.
+
+Optional shard `axes` and `axis_devices` metadata supplies the overview. Older
+captures fall back to their inline or verified loaded records; device-wide lists
+are never treated as an axis/device cross-product. Missing axis summaries remain
+explicit and their runs can still be opened. No recorded memory is displayed as
+missing evidence, never estimated from another axis.
+
+Optional unbound-finding `discovery.models` entries identify related model
+findings; `discovery.shared` identifies shared component/method findings. Both
+remain applicability-unverified and separate from exact setup/version bindings.
+Findings without discovery metadata remain accessible as uncategorized evidence.
+Original evidence links and shard fetches retain the captured commit; local
+checkout captures cannot silently fetch remote details.
+
+The browser regression fixture `tests/fixtures/browser_measurements.json` is a
+seven-setup subset captured from autolens_profiling commit
+`16471e3f6cb7acc1ebe8392af3934821bc254dea`. Its embedded shard bytes and hashes
+are unchanged; the catalogue is scoped to those setups for hermetic browser tests.
+It includes MGE/rectangular HST runs without reference candidates and without
+memory measurements, so empty-memory and useful-runtime behavior are both tested.
diff --git a/dashboard.html b/dashboard.html
index c139934..f74625f 100644
--- a/dashboard.html
+++ b/dashboard.html
@@ -485,6 +485,35 @@
   border-top: 1px solid var(--line);
   padding-top: 0.8rem;
 }
+
+.measurement-choices {
+  display: grid;
+  grid-template-columns: repeat(auto-fit, minmax(9rem, 1fr));
+  gap: 0.65rem;
+}
+.measurement-choice {
+  border: 1px solid var(--line);
+  border-radius: 8px;
+  padding: 0.65rem;
+}
+.measurement-choice p {
+  margin: 0.4rem 0 0;
+}
+.measurement-choice button {
+  width: 100%;
+  min-height: 2.75rem;
+  padding: 0.45rem;
+  font: inherit;
+  cursor: pointer;
+  color: var(--fg);
+  background: var(--bg);
+  border: 1px solid var(--line);
+  border-radius: 6px;
+}
+.measurement-choice button[aria-pressed="true"] {
+  border-color: var(--accent);
+  font-weight: 700;
+}
 </style></head><body><header class="hero"><span class="orb"><svg class="mark" viewBox="0 0 48 48" fill="none" stroke="currentColor" stroke-width="1.3" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><circle cx="24" cy="25.6" r="18.8"/><path d="M21.2,4.2 L26.8,4.2 M24,4.2 L24,6.8"/><path d="M8.4,27.2 L17.0,27.2 L19.6,22.4 L22.6,35.0 L26.4,14.8 L29.4,27.2 L39.6,27.2"/><g fill="currentColor" stroke="none"><circle cx="26.4" cy="14.8" r="1.5"/><circle cx="24" cy="4.2" r="1.3"/></g></svg></span><h1>PyAuto<b>Pulse</b><span class="kind">Profiling dashboard</span></h1><div class="rule"></div><p class="tag">Measure. Trace. Compare.</p></header><nav class="board-nav" aria-label="Board sections"><a class="board-nav-card" href="#campaigns"><span class="board-nav-label">Active campaigns</span></a><a class="board-nav-card" href="#evidence"><span class="board-nav-label">Profiling evidence</span></a></nav><main><!-- pulse-campaigns:cbea1eba629dc0064077ad5d1af613005d3a58f8a6d17b54b253eb6468e6d379 --><section class="orchestration-panel" id="orchestration-pulse" aria-labelledby="orchestration-pulse-heading" data-orchestration-panel><div class="orchestration-head"><div><h2 class="prompt-heading" id="orchestration-pulse-heading">Check your <strong>Pulse</strong></h2></div><nav class="orchestration-links" aria-label="Work on GitHub"><a href="https://github.com/PyAutoLabs/PyAutoPulse">PyAutoPulse</a><a href="https://github.com/PyAutoLabs/autolens_profiling">autolens_profiling</a></nav></div><div class="orchestration-controls"><div class="orchestration-direction"><label for="orchestration-pulse-direction">Optional direction</label><textarea id="orchestration-pulse-direction" rows="2" data-orchestration-direction placeholder="Focus on a task, project or question"></textarea></div><button type="button" class="orchestration-copy" data-orchestration-copy>Profiling Check In</button></div><details data-orchestration-preview><summary>Read the prompt</summary><label class="sr-only" for="orchestration-pulse-prompt">Exact prompt to copy</label><textarea id="orchestration-pulse-prompt" data-orchestration-prompt readonly rows="8">Use PyAutoPulse as the home for profiling work in this ongoing chat. Read PyAutoPulse/AGENTS.md and CHECKIN.md, then the campaign ledger, relevant tasks and registered project evidence. Use Brain’s profiling conductor for profiling analysis and planning, and project-owned drivers for execution.
 
 When I give no particular direction, review every open campaign and task for changes since the last check-in: measurements, jobs, PRs, releases, blockers and recorded next steps. Give me a concise campaign-by-campaign summary and a proposed priority order. Distinguish verified updates from stale, missing or unavailable evidence.
@@ -617,6 +646,113 @@
       state = {},
       generation = 0;
     const cache = new Map();
+    const axes = {
+      runtime: "Runtime",
+      breakdown: "Breakdown",
+      compile: "Compilation",
+      memory: "Memory",
+    };
+    const manifestFor = (s) =>
+      (catalogue.evidence_shards || []).find((m) => m.setup_id === s.id);
+    const recordsFor = (s) => {
+      const manifest = manifestFor(s);
+      return (
+        cache.get(manifest?.sha256)?.records ||
+        catalogue.records.filter((r) => r.setup_id === s.id)
+      );
+    };
+    const axesFor = (s) =>
+      manifestFor(s)?.axes || [...new Set(recordsFor(s).map((r) => r.axis))];
+    const hasAxis = (s, axis) => axesFor(s).includes(axis);
+    const devicesFor = (s, axis) =>
+      manifestFor(s)?.axis_devices?.[axis] || [
+        ...new Set(
+          recordsFor(s)
+            .filter((r) => r.axis === axis)
+            .map((r) => r.identity.device || "unknown"),
+        ),
+      ];
+    function rank(s, axis) {
+      if (hasAxis(s, axis)) return s.role === "reference_candidate" ? 0 : 1;
+      return manifestFor(s) ? 2 : s.role === "planned_baseline" ? 4 : 3;
+    }
+    function ordered(setups, axis) {
+      return [...setups].sort(
+        (a, b) =>
+          rank(a, axis) - rank(b, axis) ||
+          configurationLabel(a).localeCompare(configurationLabel(b)) ||
+          a.id.localeCompare(b.id),
+      );
+    }
+    function chooseAxis(setup) {
+      return (
+        Object.keys(axes).find((axis) => hasAxis(setup, axis)) || "runtime"
+      );
+    }
+    function goAxis(axis, device = "") {
+      route({
+        dataset: state.dataset,
+        model: state.model,
+        instrument: state.instrument,
+        axis,
+        device,
+      });
+    }
+    function overview(setups) {
+      const section = append(
+        results,
+        "section",
+        undefined,
+        "measurement-overview",
+      );
+      append(section, "h3", "Available measurements");
+      append(
+        section,
+        "p",
+        "Browse recorded runs by measurement and device. Runs can have different settings and revisions; they are not a combined benchmark.",
+        "axis-note",
+      );
+      const unknown = setups.filter(
+        (s) => manifestFor(s) && !axesFor(s).length,
+      );
+      if (unknown.length)
+        append(
+          section,
+          "p",
+          `${unknown.length} recorded runs have no axis summary; open a run to inspect its evidence.`,
+          "metric-meta",
+        );
+      const grid = append(section, "div", undefined, "measurement-choices");
+      for (const [axis, title] of Object.entries(axes)) {
+        const matches = setups.filter((s) => hasAxis(s, axis));
+        const card = append(grid, "div", undefined, "measurement-choice");
+        const button = append(card, "button", title);
+        button.type = "button";
+        button.dataset.axis = axis;
+        button.setAttribute("aria-pressed", String(state.axis === axis));
+        button.onclick = () => goAxis(axis);
+        append(
+          card,
+          "p",
+          matches.length
+            ? `${matches.length} recorded runs`
+            : unknown.length
+              ? "Axis coverage not recorded"
+              : "No recorded measurements",
+          "metric-meta",
+        );
+        const devices = [
+          ...new Set(matches.flatMap((s) => devicesFor(s, axis))),
+        ].sort();
+        append(
+          card,
+          "p",
+          devices.map(label).join(" · ") ||
+            (matches.length ? "Device breakdown not recorded" : ""),
+          "metric-meta",
+        );
+      }
+    }
     const names = {
       imaging: "Imaging",
       interferometer: "Interferometer",
@@ -917,7 +1053,7 @@
         append(d, "p", "Method: " + JSON.stringify(r.method), "metric-meta");
       }
     }
-    function panels(records) {
+    function panels(records, setups) {
       const axes = {
         runtime: [
           "Likelihood runtime",
@@ -939,11 +1075,36 @@
       for (const [axis, [title, note]] of Object.entries(axes)) {
         const section = disclosure(results, title);
         section.className = "metric-panel";
-        section.open = axis === "runtime";
+        section.dataset.axis = axis;
+        section.open =
+          axis ===
+          (records.some((r) => r.axis === state.axis)
+            ? state.axis
+            : Object.keys(axes).find((a) => records.some((r) => r.axis === a)));
         append(section, "p", note, "axis-note");
         const rows = records.filter((r) => r.axis === axis);
         if (!rows.length) {
-          append(section, "p", "Not measured for this configuration.", "empty");
+          const available = setups.filter((s) => hasAxis(s, axis));
+          append(
+            section,
+            "p",
+            available.length
+              ? `Not recorded in this run. ${available.length} other runs contain ${label(axis)} measurements; settings may differ.`
+              : setups.some((s) => manifestFor(s) && !axesFor(s).length)
+                ? "Other runs have no axis summary; their measurement coverage is unknown."
+                : "No recorded measurements for this model and instrument.",
+            "empty",
+          );
+          if (available.length) {
+            const browse = append(
+              section,
+              "button",
+              `Browse ${label(axis)} runs`,
+              "retry",
+            );
+            browse.type = "button";
+            browse.onclick = () => goAxis(axis);
+          }
           continue;
         }
         const groups = new Map();
@@ -1039,18 +1200,55 @@
         );
         item.evidence.forEach((ev) => link(append(d, "p"), ev.path, ev.path));
       }
-      const unbound = (catalogue.unbound_findings || []).filter((f) =>
-        f.evidence.path.includes("/" + setup.dataset + "/"),
+      const findings = catalogue.unbound_findings || [];
+      const unbound = findings.filter((f) =>
+        (f.discovery?.models || []).some(
+          (m) => m.dataset === setup.dataset && m.model === setup.model,
+        ),
       );
+      function findingList(parent, entries) {
+        for (const f of entries) {
+          append(parent, "h4", f.title);
+          append(parent, "p", f.discovery.reason);
+          append(parent, "p", f.reason, "metric-meta");
+          link(append(parent, "p"), f.evidence.path, "Original finding");
+        }
+      }
       if (unbound.length) {
         const other = disclosure(
           d,
-          "Related findings · applicability unverified",
+          `Related model findings · applicability unverified (${unbound.length})`,
         );
-        unbound.forEach((f) => {
-          append(other, "p", f.title + " — " + f.reason);
-          link(append(other, "p"), f.evidence.path, f.evidence.path);
-        });
+        other.className = "related-hazards";
+        findingList(other, unbound);
+      }
+      const shared = findings.filter((f) => f.discovery?.shared);
+      if (shared.length) {
+        const other = disclosure(
+          d,
+          `Shared component and method findings (${shared.length})`,
+        );
+        other.className = "shared-hazards";
+        append(
+          other,
+          "p",
+          "These concern shared components or methods. Their presence here does not establish that this model uses them or that this run is affected.",
+        );
+        findingList(other, shared);
+      }
+      const uncategorized = findings.filter((f) => !f.discovery);
+      if (uncategorized.length) {
+        const other = disclosure(
+          d,
+          `Uncategorized findings (${uncategorized.length})`,
+        );
+        append(
+          other,
+          "p",
+          "Model association and applicability have not been established.",
+        );
+        for (const f of uncategorized)
+          link(append(other, "p"), f.evidence.path, f.title);
       }
       const estimates = (catalogue.static_memory_estimates || []).filter(
         (e) => setup.evidence && e.evidence.path === setup.evidence.path,
@@ -1119,7 +1317,8 @@
       const instruments = [...new Set(choices.map(instrument))].sort();
       if (
         (state.setup && !choices.some((s) => s.id === state.setup)) ||
-        (state.instrument && !instruments.includes(state.instrument))
+        (state.instrument && !instruments.includes(state.instrument)) ||
+        (state.axis && !Object.hasOwn(axes, state.axis))
       ) {
         append(
           results,
@@ -1147,36 +1346,83 @@
               choices.find((s) => s.role === "reference_candidate") ||
                 choices[0],
             );
-      const rank = (s) =>
-        s.role === "reference_candidate"
-          ? catalogue.records.some(
-              (r) => r.setup_id === s.id && r.axis === "runtime",
-            )
-            ? 0
-            : 1
-          : s.role === "planned_baseline"
-            ? 3
-            : 2;
-      const variants = choices
-        .filter((s) => instrument(s) === selectedInstrument)
-        .sort(
-          (a, b) =>
-            rank(a) - rank(b) ||
-            configurationLabel(a).localeCompare(configurationLabel(b)),
+      const instrumentSetups = choices.filter(
+        (s) => instrument(s) === selectedInstrument,
+      );
+      const axis =
+        state.axis ||
+        (requested
+          ? chooseAxis(requested)
+          : chooseAxis(ordered(instrumentSetups, "runtime")[0]));
+      const devices = [
+        ...new Set(instrumentSetups.flatMap((s) => devicesFor(s, axis))),
+      ].sort();
+      if (state.device && !devices.includes(state.device)) {
+        append(
+          results,
+          "p",
+          "No recorded device matches this link. Choose a measurement to browse available runs.",
+          "empty",
+        );
+        state.instrument = selectedInstrument;
+        overview(instrumentSetups);
+        return;
+      }
+      const device = state.device || "";
+      if (
+        device &&
+        requested &&
+        manifestFor(requested) &&
+        !devicesFor(requested, axis).includes(device)
+      ) {
+        append(
+          results,
+          "p",
+          "The linked run does not record this measurement on the selected device. No substitute measurements are shown.",
+          "empty",
+        );
+        const reset = append(
+          results,
+          "button",
+          "Open the exact run without the device filter",
+          "retry",
         );
-      // Baseline is a coverage placeholder, not a fallback claim that archive evidence is accepted.
+        reset.type = "button";
+        reset.onclick = () =>
+          route({ ...state, device: "", axis: chooseAxis(requested) });
+        return;
+      }
+      const matches = ordered(
+        instrumentSetups.filter(
+          (s) =>
+            hasAxis(s, axis) &&
+            (!device || devicesFor(s, axis).includes(device)),
+        ),
+        axis,
+      );
+      // Keep explicit baseline/failed selections reachable without calling them measurements.
+      const variants = [
+        ...matches,
+        ...instrumentSetups.filter(
+          (s) => !matches.includes(s) && !axesFor(s).length,
+        ),
+      ];
+      if (requested && !variants.some((s) => s.id === requested.id))
+        variants.unshift(requested);
       const setup = requested || variants[0];
       state = {
         instance: capture.instance,
         dataset: state.dataset,
         model: state.model,
         instrument: selectedInstrument,
-        setup: setup.id,
+        axis,
+        ...(device ? { device } : {}),
+        ...(setup ? { setup: setup.id } : {}),
       };
       history.replaceState(null, "", "#" + new URLSearchParams(state));
-      const fields = append(results, "div", "", "selectors");
+      const instrumentFields = append(results, "div", "", "selectors");
       selector(
-        fields,
+        instrumentFields,
         "instrument",
         "Instrument",
         instruments.map((i) => [
@@ -1191,13 +1437,47 @@
             instrument: value,
           }),
       );
+      overview(instrumentSetups);
+      const fields = append(results, "div", "", "selectors");
+      selector(
+        fields,
+        "device",
+        "Recorded device",
+        [["", "All recorded devices"], ...devices.map((d) => [d, label(d)])],
+        device,
+        (value) => goAxis(axis, value),
+      );
+      if (!setup) {
+        append(
+          results,
+          "p",
+          "No recorded runs for this measurement. Choose another measurement above.",
+          "empty",
+        );
+        advice({ dataset: state.dataset, model: state.model });
+        evidence({ dataset: state.dataset, model: state.model }, []);
+        return;
+      }
       selector(
         fields,
         "configuration",
         "Configuration / evidence run",
         variants.map((s) => [s.id, configurationLabel(s)]),
         setup.id,
-        (value) => route({ ...state, setup: value }),
+        (value) => {
+          const selected = variants.find((s) => s.id === value);
+          const nextAxis = hasAxis(selected, axis)
+            ? axis
+            : chooseAxis(selected);
+          route({
+            ...state,
+            setup: value,
+            axis: nextAxis,
+            device: devicesFor(selected, nextAxis).includes(device)
+              ? device
+              : "",
+          });
+        },
       );
       const context = append(results, "div", "", "context");
       append(
@@ -1243,7 +1523,7 @@
             slots.length +
             " measurement slots not measured.",
         );
-        panels([]);
+        panels([], instrumentSetups);
         metadata(setup);
         advice(setup);
         evidence(setup, []);
@@ -1255,7 +1535,7 @@
       if (!manifest) {
         const inline = catalogue.records.filter((r) => r.setup_id === setup.id);
         if (inline.length) {
-          panels(inline);
+          panels(inline, instrumentSetups);
           metadata(setup);
           qualification(inline);
           advice(setup);
@@ -1272,7 +1552,7 @@
           failed.map((s) => s.status + ": " + s.reason).join("; ") ||
             "No measured evidence is available.",
         );
-        panels([]);
+        panels([], instrumentSetups);
         metadata(setup);
         advice(setup);
         evidence(setup, []);
@@ -1313,7 +1593,7 @@
           )
         )
           throw Error("Evidence does not match the selected setup.");
-        panels(shard.records);
+        panels(shard.records, instrumentSetups);
         metadata(setup);
         qualification(shard.records);
         advice(setup);
diff --git a/pulse/setup_browser.css b/pulse/setup_browser.css
index 8829acf..787d251 100644
--- a/pulse/setup_browser.css
+++ b/pulse/setup_browser.css
@@ -216,3 +216,32 @@ button.retry {
   border-top: 1px solid var(--line);
   padding-top: 0.8rem;
 }
+
+.measurement-choices {
+  display: grid;
+  grid-template-columns: repeat(auto-fit, minmax(9rem, 1fr));
+  gap: 0.65rem;
+}
+.measurement-choice {
+  border: 1px solid var(--line);
+  border-radius: 8px;
+  padding: 0.65rem;
+}
+.measurement-choice p {
+  margin: 0.4rem 0 0;
+}
+.measurement-choice button {
+  width: 100%;
+  min-height: 2.75rem;
+  padding: 0.45rem;
+  font: inherit;
+  cursor: pointer;
+  color: var(--fg);
+  background: var(--bg);
+  border: 1px solid var(--line);
+  border-radius: 6px;
+}
+.measurement-choice button[aria-pressed="true"] {
+  border-color: var(--accent);
+  font-weight: 700;
+}
diff --git a/pulse/setup_browser.js b/pulse/setup_browser.js
index 9e1611f..45e62fb 100644
--- a/pulse/setup_browser.js
+++ b/pulse/setup_browser.js
@@ -16,6 +16,113 @@
       state = {},
       generation = 0;
     const cache = new Map();
+    const axes = {
+      runtime: "Runtime",
+      breakdown: "Breakdown",
+      compile: "Compilation",
+      memory: "Memory",
+    };
+    const manifestFor = (s) =>
+      (catalogue.evidence_shards || []).find((m) => m.setup_id === s.id);
+    const recordsFor = (s) => {
+      const manifest = manifestFor(s);
+      return (
+        cache.get(manifest?.sha256)?.records ||
+        catalogue.records.filter((r) => r.setup_id === s.id)
+      );
+    };
+    const axesFor = (s) =>
+      manifestFor(s)?.axes || [...new Set(recordsFor(s).map((r) => r.axis))];
+    const hasAxis = (s, axis) => axesFor(s).includes(axis);
+    const devicesFor = (s, axis) =>
+      manifestFor(s)?.axis_devices?.[axis] || [
+        ...new Set(
+          recordsFor(s)
+            .filter((r) => r.axis === axis)
+            .map((r) => r.identity.device || "unknown"),
+        ),
+      ];
+    function rank(s, axis) {
+      if (hasAxis(s, axis)) return s.role === "reference_candidate" ? 0 : 1;
+      return manifestFor(s) ? 2 : s.role === "planned_baseline" ? 4 : 3;
+    }
+    function ordered(setups, axis) {
+      return [...setups].sort(
+        (a, b) =>
+          rank(a, axis) - rank(b, axis) ||
+          configurationLabel(a).localeCompare(configurationLabel(b)) ||
+          a.id.localeCompare(b.id),
+      );
+    }
+    function chooseAxis(setup) {
+      return (
+        Object.keys(axes).find((axis) => hasAxis(setup, axis)) || "runtime"
+      );
+    }
+    function goAxis(axis, device = "") {
+      route({
+        dataset: state.dataset,
+        model: state.model,
+        instrument: state.instrument,
+        axis,
+        device,
+      });
+    }
+    function overview(setups) {
+      const section = append(
+        results,
+        "section",
+        undefined,
+        "measurement-overview",
+      );
+      append(section, "h3", "Available measurements");
+      append(
+        section,
+        "p",
+        "Browse recorded runs by measurement and device. Runs can have different settings and revisions; they are not a combined benchmark.",
+        "axis-note",
+      );
+      const unknown = setups.filter(
+        (s) => manifestFor(s) && !axesFor(s).length,
+      );
+      if (unknown.length)
+        append(
+          section,
+          "p",
+          `${unknown.length} recorded runs have no axis summary; open a run to inspect its evidence.`,
+          "metric-meta",
+        );
+      const grid = append(section, "div", undefined, "measurement-choices");
+      for (const [axis, title] of Object.entries(axes)) {
+        const matches = setups.filter((s) => hasAxis(s, axis));
+        const card = append(grid, "div", undefined, "measurement-choice");
+        const button = append(card, "button", title);
+        button.type = "button";
+        button.dataset.axis = axis;
+        button.setAttribute("aria-pressed", String(state.axis === axis));
+        button.onclick = () => goAxis(axis);
+        append(
+          card,
+          "p",
+          matches.length
+            ? `${matches.length} recorded runs`
+            : unknown.length
+              ? "Axis coverage not recorded"
+              : "No recorded measurements",
+          "metric-meta",
+        );
+        const devices = [
+          ...new Set(matches.flatMap((s) => devicesFor(s, axis))),
+        ].sort();
+        append(
+          card,
+          "p",
+          devices.map(label).join(" · ") ||
+            (matches.length ? "Device breakdown not recorded" : ""),
+          "metric-meta",
+        );
+      }
+    }
     const names = {
       imaging: "Imaging",
       interferometer: "Interferometer",
@@ -316,7 +423,7 @@
         append(d, "p", "Method: " + JSON.stringify(r.method), "metric-meta");
       }
     }
-    function panels(records) {
+    function panels(records, setups) {
       const axes = {
         runtime: [
           "Likelihood runtime",
@@ -338,11 +445,36 @@
       for (const [axis, [title, note]] of Object.entries(axes)) {
         const section = disclosure(results, title);
         section.className = "metric-panel";
-        section.open = axis === "runtime";
+        section.dataset.axis = axis;
+        section.open =
+          axis ===
+          (records.some((r) => r.axis === state.axis)
+            ? state.axis
+            : Object.keys(axes).find((a) => records.some((r) => r.axis === a)));
         append(section, "p", note, "axis-note");
         const rows = records.filter((r) => r.axis === axis);
         if (!rows.length) {
-          append(section, "p", "Not measured for this configuration.", "empty");
+          const available = setups.filter((s) => hasAxis(s, axis));
+          append(
+            section,
+            "p",
+            available.length
+              ? `Not recorded in this run. ${available.length} other runs contain ${label(axis)} measurements; settings may differ.`
+              : setups.some((s) => manifestFor(s) && !axesFor(s).length)
+                ? "Other runs have no axis summary; their measurement coverage is unknown."
+                : "No recorded measurements for this model and instrument.",
+            "empty",
+          );
+          if (available.length) {
+            const browse = append(
+              section,
+              "button",
+              `Browse ${label(axis)} runs`,
+              "retry",
+            );
+            browse.type = "button";
+            browse.onclick = () => goAxis(axis);
+          }
           continue;
         }
         const groups = new Map();
@@ -438,18 +570,55 @@
         );
         item.evidence.forEach((ev) => link(append(d, "p"), ev.path, ev.path));
       }
-      const unbound = (catalogue.unbound_findings || []).filter((f) =>
-        f.evidence.path.includes("/" + setup.dataset + "/"),
+      const findings = catalogue.unbound_findings || [];
+      const unbound = findings.filter((f) =>
+        (f.discovery?.models || []).some(
+          (m) => m.dataset === setup.dataset && m.model === setup.model,
+        ),
       );
+      function findingList(parent, entries) {
+        for (const f of entries) {
+          append(parent, "h4", f.title);
+          append(parent, "p", f.discovery.reason);
+          append(parent, "p", f.reason, "metric-meta");
+          link(append(parent, "p"), f.evidence.path, "Original finding");
+        }
+      }
       if (unbound.length) {
         const other = disclosure(
           d,
-          "Related findings · applicability unverified",
+          `Related model findings · applicability unverified (${unbound.length})`,
+        );
+        other.className = "related-hazards";
+        findingList(other, unbound);
+      }
+      const shared = findings.filter((f) => f.discovery?.shared);
+      if (shared.length) {
+        const other = disclosure(
+          d,
+          `Shared component and method findings (${shared.length})`,
         );
-        unbound.forEach((f) => {
-          append(other, "p", f.title + " — " + f.reason);
-          link(append(other, "p"), f.evidence.path, f.evidence.path);
-        });
+        other.className = "shared-hazards";
+        append(
+          other,
+          "p",
+          "These concern shared components or methods. Their presence here does not establish that this model uses them or that this run is affected.",
+        );
+        findingList(other, shared);
+      }
+      const uncategorized = findings.filter((f) => !f.discovery);
+      if (uncategorized.length) {
+        const other = disclosure(
+          d,
+          `Uncategorized findings (${uncategorized.length})`,
+        );
+        append(
+          other,
+          "p",
+          "Model association and applicability have not been established.",
+        );
+        for (const f of uncategorized)
+          link(append(other, "p"), f.evidence.path, f.title);
       }
       const estimates = (catalogue.static_memory_estimates || []).filter(
         (e) => setup.evidence && e.evidence.path === setup.evidence.path,
@@ -518,7 +687,8 @@
       const instruments = [...new Set(choices.map(instrument))].sort();
       if (
         (state.setup && !choices.some((s) => s.id === state.setup)) ||
-        (state.instrument && !instruments.includes(state.instrument))
+        (state.instrument && !instruments.includes(state.instrument)) ||
+        (state.axis && !Object.hasOwn(axes, state.axis))
       ) {
         append(
           results,
@@ -546,36 +716,83 @@
               choices.find((s) => s.role === "reference_candidate") ||
                 choices[0],
             );
-      const rank = (s) =>
-        s.role === "reference_candidate"
-          ? catalogue.records.some(
-              (r) => r.setup_id === s.id && r.axis === "runtime",
-            )
-            ? 0
-            : 1
-          : s.role === "planned_baseline"
-            ? 3
-            : 2;
-      const variants = choices
-        .filter((s) => instrument(s) === selectedInstrument)
-        .sort(
-          (a, b) =>
-            rank(a) - rank(b) ||
-            configurationLabel(a).localeCompare(configurationLabel(b)),
+      const instrumentSetups = choices.filter(
+        (s) => instrument(s) === selectedInstrument,
+      );
+      const axis =
+        state.axis ||
+        (requested
+          ? chooseAxis(requested)
+          : chooseAxis(ordered(instrumentSetups, "runtime")[0]));
+      const devices = [
+        ...new Set(instrumentSetups.flatMap((s) => devicesFor(s, axis))),
+      ].sort();
+      if (state.device && !devices.includes(state.device)) {
+        append(
+          results,
+          "p",
+          "No recorded device matches this link. Choose a measurement to browse available runs.",
+          "empty",
+        );
+        state.instrument = selectedInstrument;
+        overview(instrumentSetups);
+        return;
+      }
+      const device = state.device || "";
+      if (
+        device &&
+        requested &&
+        manifestFor(requested) &&
+        !devicesFor(requested, axis).includes(device)
+      ) {
+        append(
+          results,
+          "p",
+          "The linked run does not record this measurement on the selected device. No substitute measurements are shown.",
+          "empty",
         );
-      // Baseline is a coverage placeholder, not a fallback claim that archive evidence is accepted.
+        const reset = append(
+          results,
+          "button",
+          "Open the exact run without the device filter",
+          "retry",
+        );
+        reset.type = "button";
+        reset.onclick = () =>
+          route({ ...state, device: "", axis: chooseAxis(requested) });
+        return;
+      }
+      const matches = ordered(
+        instrumentSetups.filter(
+          (s) =>
+            hasAxis(s, axis) &&
+            (!device || devicesFor(s, axis).includes(device)),
+        ),
+        axis,
+      );
+      // Keep explicit baseline/failed selections reachable without calling them measurements.
+      const variants = [
+        ...matches,
+        ...instrumentSetups.filter(
+          (s) => !matches.includes(s) && !axesFor(s).length,
+        ),
+      ];
+      if (requested && !variants.some((s) => s.id === requested.id))
+        variants.unshift(requested);
       const setup = requested || variants[0];
       state = {
         instance: capture.instance,
         dataset: state.dataset,
         model: state.model,
         instrument: selectedInstrument,
-        setup: setup.id,
+        axis,
+        ...(device ? { device } : {}),
+        ...(setup ? { setup: setup.id } : {}),
       };
       history.replaceState(null, "", "#" + new URLSearchParams(state));
-      const fields = append(results, "div", "", "selectors");
+      const instrumentFields = append(results, "div", "", "selectors");
       selector(
-        fields,
+        instrumentFields,
         "instrument",
         "Instrument",
         instruments.map((i) => [
@@ -590,13 +807,47 @@
             instrument: value,
           }),
       );
+      overview(instrumentSetups);
+      const fields = append(results, "div", "", "selectors");
+      selector(
+        fields,
+        "device",
+        "Recorded device",
+        [["", "All recorded devices"], ...devices.map((d) => [d, label(d)])],
+        device,
+        (value) => goAxis(axis, value),
+      );
+      if (!setup) {
+        append(
+          results,
+          "p",
+          "No recorded runs for this measurement. Choose another measurement above.",
+          "empty",
+        );
+        advice({ dataset: state.dataset, model: state.model });
+        evidence({ dataset: state.dataset, model: state.model }, []);
+        return;
+      }
       selector(
         fields,
         "configuration",
         "Configuration / evidence run",
         variants.map((s) => [s.id, configurationLabel(s)]),
         setup.id,
-        (value) => route({ ...state, setup: value }),
+        (value) => {
+          const selected = variants.find((s) => s.id === value);
+          const nextAxis = hasAxis(selected, axis)
+            ? axis
+            : chooseAxis(selected);
+          route({
+            ...state,
+            setup: value,
+            axis: nextAxis,
+            device: devicesFor(selected, nextAxis).includes(device)
+              ? device
+              : "",
+          });
+        },
       );
       const context = append(results, "div", "", "context");
       append(
@@ -642,7 +893,7 @@
             slots.length +
             " measurement slots not measured.",
         );
-        panels([]);
+        panels([], instrumentSetups);
         metadata(setup);
         advice(setup);
         evidence(setup, []);
@@ -654,7 +905,7 @@
       if (!manifest) {
         const inline = catalogue.records.filter((r) => r.setup_id === setup.id);
         if (inline.length) {
-          panels(inline);
+          panels(inline, instrumentSetups);
           metadata(setup);
           qualification(inline);
           advice(setup);
@@ -671,7 +922,7 @@
           failed.map((s) => s.status + ": " + s.reason).join("; ") ||
             "No measured evidence is available.",
         );
-        panels([]);
+        panels([], instrumentSetups);
         metadata(setup);
         advice(setup);
         evidence(setup, []);
@@ -712,7 +963,7 @@
           )
         )
           throw Error("Evidence does not match the selected setup.");
-        panels(shard.records);
+        panels(shard.records, instrumentSetups);
         metadata(setup);
         qualification(shard.records);
         advice(setup);
diff --git a/tests/browser_fixture.py b/tests/browser_fixture.py
index a9f59cc..137a986 100644
--- a/tests/browser_fixture.py
+++ b/tests/browser_fixture.py
@@ -49,6 +49,45 @@ def write(destination):
     inline.doc.pop("navigation")
     (destination / "inline.html").write_text(board.render_html([inline]))
 
+    grouped = copy.deepcopy(inline)
+    record = grouped.doc["records"][0]
+    grouped.doc["records"] = []
+    for metric, value, statistic in [
+        ("single_call", 1, "median"),
+        ("single_call", 2, "mean"),
+        ("batch_wall", 10, "median"),
+        ("batch_per_call", 0.5, "median"),
+    ]:
+        row = copy.deepcopy(record)
+        row.update(
+            id=metric + statistic,
+            axis="runtime",
+            metric=metric,
+            unit="s",
+            measurement={metric: value},
+        )
+        row["method"]["statistic"] = statistic
+        grouped.doc["records"].append(row)
+    (destination / "grouping.html").write_text(board.render_html([grouped]))
+
+    real = json.loads((Path(__file__).parent / "fixtures/browser_measurements.json").read_text())
+    for name, text in real["shards"].items():
+        target = destination / name
+        target.parent.mkdir(parents=True, exist_ok=True)
+        target.write_text(text)
+    captured = copy.deepcopy(snapshots[0])
+    captured.doc = real["catalogue"]
+    captured.commit = real["capture_commit"]
+    (destination / "measurements.html").write_text(board.render_html([captured]))
+    legacy = copy.deepcopy(captured)
+    for manifest in legacy.doc["evidence_shards"]:
+        manifest.pop("axis_devices", None)
+    (destination / "legacy-devices.html").write_text(board.render_html([legacy]))
+    for manifest in legacy.doc["evidence_shards"]:
+        manifest.pop("axes", None)
+    legacy.doc["records"] = []
+    (destination / "unknown-axes.html").write_text(board.render_html([legacy]))
+
 
 if __name__ == "__main__":
     write(Path(sys.argv[1]))
diff --git a/tests/browser_setup.cjs b/tests/browser_setup.cjs
index 4634ed6..64ee7df 100644
--- a/tests/browser_setup.cjs
+++ b/tests/browser_setup.cjs
@@ -34,6 +34,9 @@ const { execFileSync } = require("node:child_process");
     const page = await context.newPage(),
       errors = [];
     page.on("pageerror", (error) => errors.push(error.message));
+    const real = JSON.parse(
+      fs.readFileSync("tests/fixtures/browser_measurements.json"),
+    );
     let corrupt = false,
       delay = false,
       requests = [];
@@ -43,7 +46,9 @@ const { execFileSync } = require("node:child_process");
         const url = route.request().url();
         requests.push(url);
         assert(
-          url.includes("/" + "b".repeat(40) + "/dashboard/catalogue/shards/"),
+          ["b".repeat(40), real.capture_commit].some((commit) =>
+            url.includes("/" + commit + "/dashboard/catalogue/shards/"),
+          ),
         );
         if (delay) await new Promise((resolve) => setTimeout(resolve, 250));
         await route.fulfill({
@@ -51,7 +56,10 @@ const { execFileSync } = require("node:child_process");
           body: corrupt
             ? "{}"
             : fs.readFileSync(
-                path.join(dir, "catalogue/shards/" + "a".repeat(20) + ".json"),
+                path.join(
+                  dir,
+                  "catalogue/shards/" + new URL(url).pathname.split("/").at(-1),
+                ),
               ),
         });
       },
@@ -224,6 +232,238 @@ const { execFileSync } = require("node:child_process");
           `overflow at ${width}/${colorScheme}`,
         );
       }
+    // Legacy batch semantics and different methods must retain separate bar scales.
+    await page.goto(base + "/grouping.html#" + new URL(selected).hash.slice(1));
+    await root.locator(".metric-value").first().waitFor();
+    const runtimePanel = root.locator('.metric-panel[data-axis="runtime"]');
+    assert.equal(await runtimePanel.locator(".metric-list").count(), 4);
+    assert.match(await runtimePanel.innerText(), /Batch wall time/);
+    assert.match(await runtimePanel.innerText(), /Per-replica batch cost/);
+    assert.equal(
+      await runtimePanel
+        .locator(".metric-meta")
+        .filter({ hasText: /Single-call observations/ })
+        .count(),
+      2,
+    );
+    assert.deepEqual(
+      await runtimePanel
+        .locator(".bar")
+        .evaluateAll((ns) => ns.map((n) => n.style.width)),
+      ["100%", "100%", "100%", "100%"],
+    );
+    await root
+      .locator('.measurement-choice button[data-axis="memory"]')
+      .click();
+    await root
+      .getByText("No recorded runs for this measurement.", { exact: false })
+      .waitFor();
+    assert.equal(await root.locator(".metric-value").count(), 0);
+    // Real captured evidence: no reference candidate must still show useful values.
+    const realURL = (params, file = "measurements.html") =>
+      base +
+      "/" +
+      file +
+      "#" +
+      new URLSearchParams({
+        instance: "lens",
+        dataset: "imaging",
+        instrument: "hst",
+        ...params,
+      });
+    const ready = async () =>
+      page.waitForFunction(() => {
+        const results = document.querySelector(
+          '[data-setup-browser="lens"] [data-id="results"]',
+        );
+        return (
+          results &&
+          results.querySelector('[data-id="configuration"]') &&
+          !results.hasAttribute("aria-busy")
+        );
+      });
+    for (const model of ["mge", "rectangular"]) {
+      await page.goto(realURL({ model }));
+      await ready();
+      assert(
+        await root
+          .locator('.metric-panel[data-axis="runtime"][open] .metric-value')
+          .count(),
+      );
+      assert.equal(await root.locator(".measurement-choice button").count(), 4);
+      for (const axis of ["breakdown", "compile", "memory", "runtime"]) {
+        await root
+          .locator('.measurement-choice button[data-axis="' + axis + '"]')
+          .click();
+        const available = real.catalogue.evidence_shards.some(
+          (m) =>
+            m.setup_id.startsWith("imaging/" + model + "/hst/") &&
+            m.axes.includes(axis),
+        );
+        if (!available) {
+          await root
+            .getByText("No recorded runs for this measurement.", {
+              exact: false,
+            })
+            .waitFor();
+          assert.equal(await root.locator(".metric-value").count(), 0);
+          continue;
+        }
+        await ready();
+        const id = await root.locator('[data-id="configuration"]').inputValue();
+        const manifest = real.catalogue.evidence_shards.find(
+          (m) => m.setup_id === id,
+        );
+        assert(manifest.axes.includes(axis));
+        assert(
+          await root
+            .locator(
+              '.metric-panel[data-axis="' + axis + '"][open] .metric-value',
+            )
+            .count(),
+        );
+        const shard = JSON.parse(real.shards[manifest.path]);
+        const values = await root
+          .locator(".metric-value")
+          .evaluateAll((nodes) =>
+            nodes.map((n) => n.dataset.value + " " + n.dataset.unit),
+          );
+        assert.deepEqual(
+          values.sort(),
+          shard.records
+            .map((r) => String(r.measurement[r.metric]) + " " + r.unit)
+            .sort(),
+        );
+      }
+      // Preserve a compatible device filter when choosing another run.
+      const device = await root
+        .locator('[data-id="device"] option')
+        .nth(1)
+        .getAttribute("value");
+      await root.locator('[data-id="device"]').selectOption(device);
+      await ready();
+      const options = await root
+        .locator('[data-id="configuration"] option')
+        .evaluateAll((ns) => ns.map((n) => n.value));
+      assert(options.length >= 2);
+      await root.locator('[data-id="configuration"]').selectOption(options[1]);
+      await ready();
+      assert.equal(
+        await root.locator('[data-id="device"]').inputValue(),
+        device,
+      );
+      assert.equal(new URL(page.url()).hash.includes("device=" + device), true);
+      assert.equal(
+        await root.locator(".related-hazards").count(),
+        model === "rectangular" ? 1 : 0,
+      );
+      assert.equal(await root.locator(".shared-hazards").count(), 1);
+      const guidance = root.locator("details").filter({
+        has: page.locator("summary", {
+          hasText: /^Hazards and setup guidance$/,
+        }),
+      });
+      await guidance.locator(":scope > summary").click();
+      assert.match(
+        await guidance.innerText(),
+        /not evidence that it is hazard-free/,
+      );
+      await root.locator(".shared-hazards > summary").click();
+      assert.match(
+        await root.locator(".shared-hazards").innerText(),
+        /does not establish/,
+      );
+      for (const width of [320, 390, 768, 1280]) {
+        await page.setViewportSize({ width, height: 1000 });
+        assert(
+          await page.evaluate(
+            () => document.documentElement.scrollWidth <= innerWidth + 1,
+          ),
+          `real ${model} overflow ${width}`,
+        );
+      }
+      const before = page.url();
+      await root
+        .locator('.measurement-choice button[data-axis="breakdown"]')
+        .focus();
+      await page.keyboard.press("Enter");
+      await ready();
+      await page.goBack();
+      await ready();
+      assert.equal(page.url(), before);
+    }
+    const breakdown = real.catalogue.evidence_shards.find(
+      (m) =>
+        m.setup_id.startsWith("imaging/mge/") &&
+        m.axes.includes("breakdown") &&
+        !m.axes.includes("runtime"),
+    );
+    await page.goto(realURL({ model: "mge", setup: breakdown.setup_id }));
+    await ready();
+    assert(
+      await root
+        .locator('.metric-panel[data-axis="breakdown"][open] .metric-value')
+        .count(),
+    );
+    assert.equal(
+      await root.locator('[data-id="configuration"]').inputValue(),
+      breakdown.setup_id,
+    );
+    await root.locator('.metric-panel[data-axis="runtime"] > summary').click();
+    assert.match(
+      await root.locator('.metric-panel[data-axis="runtime"]').innerText(),
+      /other runs contain/,
+    );
+    const cpuBreakdown = real.catalogue.evidence_shards.find(
+      (m) =>
+        m.setup_id.startsWith("imaging/rectangular/") &&
+        m.axis_devices.breakdown?.includes("cpu"),
+    );
+    await page.goto(
+      realURL({
+        model: "rectangular",
+        setup: cpuBreakdown.setup_id,
+        axis: "breakdown",
+        device: "a100",
+      }),
+    );
+    await root
+      .getByText("The linked run does not record this measurement", {
+        exact: false,
+      })
+      .waitFor();
+    assert.equal(await root.locator(".metric-value").count(), 0);
+    await root
+      .getByRole("button", {
+        name: "Open the exact run without the device filter",
+      })
+      .click();
+    await ready();
+    assert.equal(
+      await root.locator('[data-id="configuration"]').inputValue(),
+      cpuBreakdown.setup_id,
+    );
+    // Unknown device is never silently replaced with another run.
+    await page.goto(realURL({ model: "mge", device: "not-recorded" }));
+    await root
+      .getByText("No recorded device matches this link.", { exact: false })
+      .waitFor();
+    assert.equal(await root.locator(".metric-value").count(), 0);
+    await root
+      .locator('.measurement-choice button[data-axis="runtime"]')
+      .click();
+    await ready();
+    // Optional producer metadata: older captures retain working evidence navigation.
+    await page.goto(realURL({ model: "mge" }, "legacy-devices.html"));
+    await ready();
+    assert(await root.locator(".metric-panel[open] .metric-value").count());
+    await page.goto(realURL({ model: "mge" }, "unknown-axes.html"));
+    await ready();
+    assert(await root.locator(".metric-panel[open] .metric-value").count());
+    assert.match(
+      await root.locator(".measurement-overview").innerText(),
+      /no axis summary/,
+    );
     assert.deepEqual(errors, []);
     await context.close();
     const nojs = await browser.newContext({ javaScriptEnabled: false });
@@ -243,7 +483,7 @@ const { execFileSync } = require("node:child_process");
     );
     await nojs.close();
     console.log(
-      "PASS: pinned shards, hash refusal/retry, stale links, race, multi-project history, inline v2, clipboard, campaign routing, responsive light/dark, no-JS",
+      "PASS: real MGE/rectangular axis navigation, exact values, absent memory, device persistence, qualified hazards, exact-link recovery, older metadata; pinned shards, hash refusal/retry, stale links, race, multi-project history, inline v2, clipboard, campaign routing, responsive light/dark, no-JS",
     );
   } finally {
     if (browser) await browser.close();
diff --git a/tests/fixtures/browser_measurements.json b/tests/fixtures/browser_measurements.json
new file mode 100644
index 0000000..b6ebf6e
--- /dev/null
+++ b/tests/fixtures/browser_measurements.json
@@ -0,0 +1 @@
+{"source":"PyAutoLabs/autolens_profiling","capture_commit":"16471e3f6cb7acc1ebe8392af3934821bc254dea","catalogue":{"archive_record_count":20709,"comparison_policy":{"id":"no-temporal-comparisons"},"comparisons":[],"evidence_shards":[{"axes":["runtime"],"axis_devices":{"runtime":["cpu"]},"devices":["cpu"],"path":"catalogue/shards/a4a3577448e2387a5e1f.json","precisions":["float64"],"records":3,"setup_id":"imaging/mge/hst/b507dea06deef9a3d4a6","sha256":"dd9a7cf4ffb51ae6b072d46055177e7722b9a0faf6e60c86a15f681c32d1d0a3"},{"axes":["runtime"],"axis_devices":{"runtime":["cpu"]},"devices":["cpu"],"path":"catalogue/shards/bdd10082f82baec9104c.json","precisions":["float64"],"records":3,"setup_id":"imaging/mge/hst/c013d586e4b27188c85a","sha256":"374be1fe99f51baaecb5b5d2ce84113ad3b899b7944136c43439f8379fcf96e9"},{"axes":["breakdown"],"axis_devices":{"breakdown":["cpu"]},"devices":["cpu"],"path":"catalogue/shards/0bab4cd19f0d67badc7b.json","precisions":["precision not recorded"],"records":9,"setup_id":"imaging/mge/hst/3410406f70c062bc22a8","sha256":"646eea3e59b16ea50458b2ba8692a52e9bddb1656410a3125a6d2767a8a6cadf"},{"axes":["breakdown","compile"],"axis_devices":{"breakdown":["cpu"],"compile":["cpu"]},"devices":["cpu"],"path":"catalogue/shards/33259f102f531dc5459c.json","precisions":["float64"],"records":4,"setup_id":"imaging/mge/hst/b96665c290af9cb918c0","sha256":"8166ef0e88a7fadd6ee4bf2345cad0f31e6c87d05e91248f2de76f3b38975906"},{"axes":["breakdown","runtime"],"axis_devices":{"breakdown":["cpu"],"runtime":["cpu"]},"devices":["cpu"],"path":"catalogue/shards/37901eca52be7b7e1992.json","precisions":["precision not recorded"],"records":25,"setup_id":"imaging/rectangular/hst/5bc82443b3661250f9c8","sha256":"057f48b6a70b4019e806aceeda4a087b87c6905b3b6e411b3595334908382573"},{"axes":["breakdown","runtime"],"axis_devices":{"breakdown":["cpu"],"runtime":["cpu"]},"devices":["cpu"],"path":"catalogue/shards/3137f16bcc75df56ff7e.json","precisions":["precision not recorded"],"records":25,"setup_id":"imaging/rectangular/hst/3e9dd14df5f1c679cb10","sha256":"a230a0bdeaef719b6b2d87e18e10b3a3d4ccecefeb4afd4372df8e709c863276"},{"axes":["breakdown","compile"],"axis_devices":{"breakdown":["a100"],"compile":["a100"]},"devices":["a100"],"path":"catalogue/shards/824a5fd973244095bd3a.json","precisions":["float64"],"records":36,"setup_id":"imaging/rectangular/hst/b9c3a1e9ced12e87ea7c","sha256":"da30efc283b22d5f22cc00b983cf979dac16eb8f322a9be0e33e9c5d0ae62160"}],"evidence_updated_at":null,"evidence_updated_at_reason":"No common measurement wall-clock across legacy evidence; inspect each record.","generated_at":"2026-10-07T07:00:40Z","hazards":[],"limitations":["Legacy evidence remains unreviewed; no new baseline has been accepted.","Source-row isolation prevents cross-file joins where complete configuration identity is unknown.","The v1 production feed remains published during migration; this is the companion v2 catalogue.","Indexed-only evidence and static estimates are not successful measurements or measured peak VRAM."],"navigation":[{"category":"scientific_entrypoint","dataset":"imaging","legacy_paths":["scripts/imaging/hazards/mge_nnls_capture.py"],"measurement":"hazards_nnls_capture","model":"mge","path":"scripts/imaging/mge/hazards_nnls_capture.py"},{"category":"scientific_entrypoint","dataset":"imaging","legacy_paths":["scripts/imaging/likelihood_breakdown/mge.py"],"measurement":"likelihood_breakdown","model":"mge","path":"scripts/imaging/mge/likelihood_breakdown.py"},{"category":"scientific_entrypoint","dataset":"imaging","legacy_paths":["scripts/imaging/likelihood_runtime/mge.py"],"measurement":"likelihood_runtime","model":"mge","path":"scripts/imaging/mge/likelihood_runtime.py"},{"category":"scientific_entrypoint","dataset":"imaging","legacy_paths":["scripts/imaging/quick_update/mge.py"],"measurement":"quick_update","model":"mge","path":"scripts/imaging/mge/quick_update.py"},{"category":"scientific_entrypoint","dataset":"imaging","legacy_paths":["scripts/imaging/hazards/pixelization.py"],"measurement":"hazards","model":"rectangular","path":"scripts/imaging/rectangular/hazards.py"},{"category":"scientific_entrypoint","dataset":"imaging","legacy_paths":["scripts/imaging/likelihood_breakdown/pixelization.py"],"measurement":"likelihood_breakdown","model":"rectangular","path":"scripts/imaging/rectangular/likelihood_breakdown.py"},{"category":"scientific_entrypoint","dataset":"imaging","legacy_paths":["scripts/imaging/likelihood_breakdown/pixelization_numba.py"],"measurement":"likelihood_breakdown_numba","model":"rectangular","path":"scripts/imaging/rectangular/likelihood_breakdown_numba.py"},{"category":"scientific_entrypoint","dataset":"imaging","legacy_paths":["scripts/imaging/likelihood_runtime/pixelization.py"],"measurement":"likelihood_runtime","model":"rectangular","path":"scripts/imaging/rectangular/likelihood_runtime.py"},{"category":"scientific_entrypoint","dataset":"imaging","legacy_paths":["scripts/imaging/likelihood_runtime/pixelization_numba.py"],"measurement":"likelihood_runtime_numba","model":"rectangular","path":"scripts/imaging/rectangular/likelihood_runtime_numba.py"},{"category":"scientific_entrypoint","dataset":"imaging","legacy_paths":["scripts/imaging/likelihood_runtime/pixelization_numba_mge_mass.py"],"measurement":"likelihood_runtime_numba_mge_mass","model":"rectangular","path":"scripts/imaging/rectangular/likelihood_runtime_numba_mge_mass.py"},{"category":"scientific_entrypoint","dataset":"imaging","legacy_paths":["scripts/imaging/parallel_scaling/pixelization_numba.py"],"measurement":"parallel_scaling_numba","model":"rectangular","path":"scripts/imaging/rectangular/parallel_scaling_numba.py"}],"planned_cells":[],"producer_revision":"fef5f28da520df4a357805647cb0f093d5b22583","project":"autolens_profiling","recommendations":[],"records":[],"schema":"profiling-summary","scope":"setup-catalogue","selections":[],"setups":[{"configuration":{"fallback_row_budget":{"unit":"recorded","value":1},"fallback_rows":{"unit":"recorded","value":true},"image_pixels_masked":{"unit":"count","value":15361},"image_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"mask_radius_arcsec":{"unit":"recorded","value":3.5},"memo":{"unit":"recorded","value":"library_default (inert on the JAX path)"},"mesh":{"unit":"recorded","value":"rectangular"},"mesh_shape":{"unit":"recorded","value":[39,39]},"n_vis":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"over_sample_size_lp_rule":{"unit":"recorded","value":{"centre":[0.0,0.0],"radial_list":[0.3,0.6],"sub_size_list":[4,2,2]}},"over_sampled_pixels":{"unit":"recorded","value":62752},"oversampled_pixels":{"unit":"recorded","value":62752},"oversampling":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"dimensionless","value":null},"pass_budget":{"unit":"recorded","value":7},"pass_budget_max_diagnostics":{"unit":"recorded","value":8},"pixel_scale_arcsec":{"unit":"recorded","value":0.05},"preloads":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"psf_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"rect_mesh":{"unit":"recorded","value":"bilinear"},"regularization":{"unit":"name","value":{"coefficient":1.0,"scheme":"constant"}},"solver":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"source_pixels":{"unit":"count","value":1521},"source_pixels_requested":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"recorded","value":null},"thread_env":{"unit":"recorded","value":{"n_threads":null,"note":"Not pinned (legacy variant): recorded as found.","overridden":{},"preexisting":{},"set_to":null,"vars":["OPENBLAS_NUM_THREADS","MKL_NUM_THREADS","OMP_NUM_THREADS","VECLIB_MAXIMUM_THREADS","NUMEXPR_NUM_THREADS"]}},"transformer":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"vmap_batch":{"unit":"recorded","value":16}},"configuration_id":"b9c3a1e9ced12e87ea7c","dataset":"imaging","evidence":{"fragment":null,"path":"results/breakdown/imaging/fixed_light_library_rectangular_hpc_a100_fp64_fixed_light_library.json"},"id":"imaging/rectangular/hst/b9c3a1e9ced12e87ea7c","identity_limitations":"Isolated to source row: legacy metadata is insufficient for cross-file joins.","instrument":"hst","label":"rectangular \u00b7 hst","model":"rectangular","role":"legacy_or_experimental"},{"configuration":{"image_pixels_masked":{"unit":"count","value":15361},"image_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"linear_gaussians":{"unit":"recorded","value":0},"mask_radius_arcsec":{"unit":"recorded","value":3.5},"n_vis":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"over_sampled_pixels":{"unit":"recorded","value":17980},"oversampled_pixels":{"unit":"recorded","value":17980},"oversampling":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"dimensionless","value":null},"pixel_scale_arcsec":{"unit":"recorded","value":0.05},"preloads":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"psf_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"regularization":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"solver":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"source_pixels":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"transformer":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null}},"configuration_id":"3410406f70c062bc22a8","dataset":"imaging","evidence":{"fragment":null,"path":"results/breakdown/imaging/mge_breakdown_hst_v2026.5.29.4.json"},"id":"imaging/mge/hst/3410406f70c062bc22a8","identity_limitations":"Isolated to source row: legacy metadata is insufficient for cross-file joins.","instrument":"hst","label":"mge \u00b7 hst","model":"mge","role":"legacy_or_experimental"},{"configuration":{"adapt_snr_cap":{"unit":"recorded","value":3.0},"image_pixels_masked":{"unit":"count","value":15361},"image_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"lens_light":{"unit":"recorded","value":"mge_60_linear_2_basis"},"mask_radius_arcsec":{"unit":"recorded","value":3.5},"memo":{"unit":"recorded","value":"off"},"memo_provenance":{"unit":"recorded","value":{"env_AUTOARRAY_NNLS_WARM_START":"0","env_before":null,"note":"Both gates are set for memo=off: the Settings flag and the AUTOARRAY_NNLS_WARM_START env kill-switch (autoarray/inversion/inversion/nnls_memo.py:63). settings_nnls_warm_start_memo is read back off the constructed Settings, so it records what took effect. The library default is true and both production projects leave it unset.","requested":"off","settings_nnls_warm_start_memo":false}},"mesh":{"unit":"recorded","value":{"kind":"rectangular","shape":[32,32],"source_pixels":1024}},"mesh_kind":{"unit":"recorded","value":"rectangular"},"mesh_shape":{"unit":"recorded","value":[32,32]},"mge_gaussian_per_basis":{"unit":"recorded","value":2},"mge_total_gaussians":{"unit":"recorded","value":30},"n_instances":{"unit":"recorded","value":20},"n_vis":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"omp_num_threads":{"unit":"recorded","value":"1"},"over_sample_size_lp_rule":{"unit":"recorded","value":{"centre":[0.0,0.0],"radial_list":[0.1,0.3],"sub_size_list":[4,2,2]}},"over_sample_size_pixelization_rule":{"unit":"recorded","value":{"source_snr_cut":3.0,"sub_size_above":4,"sub_size_below":2}},"over_sampled_pixels":{"unit":"recorded","value":61600},"oversampled_pixels":{"unit":"recorded","value":61600},"oversampling":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"dimensionless","value":null},"pixel_scale_arcsec":{"unit":"recorded","value":0.05},"positions_penalty":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"recorded","value":null},"preloads":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"preset":{"unit":"recorded","value":"hst_rect_adapt"},"provenance":{"unit":"recorded","value":"subhalo_validation/scripts/pipelines/rectangular_adapt.py (rect_adapt source_pix[2], job 342311): RectangularBilinearAdaptImage shape (32, 32) (MESH_PIXELS_YX :38), regularization Adapt; the rest of the stage (adapt S/N cap, over-sampling, MGE, threads) as hst_source_pix_2"},"psf_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"rect_mesh":{"unit":"recorded","value":"bilinear"},"regularization":{"unit":"name","value":{"coefficient":1.0,"free":false,"scheme":"adapt"}},"sequence":{"unit":"recorded","value":{"kind":"iid","seed":235,"unit_high":0.6,"unit_low":0.4}},"solver":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"source_pixels":{"unit":"count","value":1024},"thread_env":{"unit":"recorded","value":{"n_threads":1,"note":"Set by _production_config.pin_thread_env before numpy import; mirrors the production SLURM submit scripts.","overridden":{},"preexisting":{"MKL_NUM_THREADS":"1","NUMEXPR_NUM_THREADS":"1","OMP_NUM_THREADS":"1","OPENBLAS_NUM_THREADS":"1","VECLIB_MAXIMUM_THREADS":"1"},"set_to":"1","vars":["OPENBLAS_NUM_THREADS","MKL_NUM_THREADS","OMP_NUM_THREADS","VECLIB_MAXIMUM_THREADS","NUMEXPR_NUM_THREADS"]}},"transformer":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"use_jax":{"unit":"recorded","value":false},"variant":{"unit":"recorded","value":"production"}},"configuration_id":"5bc82443b3661250f9c8","dataset":"imaging","evidence":{"fragment":null,"path":"results/breakdown/imaging/pixelization_numba_breakdown_hst_v2026.8.17.1.json"},"id":"imaging/rectangular/hst/5bc82443b3661250f9c8","identity_limitations":"Isolated to source row: legacy metadata is insufficient for cross-file joins.","instrument":"hst","label":"rectangular \u00b7 hst","model":"rectangular","role":"legacy_or_experimental"},{"configuration":{"image_pixels_masked":{"unit":"count","value":15361},"image_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"lens_light":{"unit":"recorded","value":"mge_60_linear"},"mask_radius_arcsec":{"unit":"recorded","value":3.5},"mesh_shape":{"unit":"recorded","value":[28,28]},"n_vis":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"omp_num_threads":{"unit":"recorded","value":"1"},"over_sampled_pixels":{"unit":"recorded","value":17980},"oversampled_pixels":{"unit":"recorded","value":17980},"oversampling":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"dimensionless","value":null},"pixel_scale_arcsec":{"unit":"recorded","value":0.05},"preloads":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"psf_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"rect_mesh":{"unit":"recorded","value":"rtu"},"regularization":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"solver":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"source_pixels":{"unit":"count","value":784},"transformer":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"use_jax":{"unit":"recorded","value":false}},"configuration_id":"3e9dd14df5f1c679cb10","dataset":"imaging","evidence":{"fragment":null,"path":"results/breakdown/imaging/pixelization_numba_breakdown_hst_v2026.8.17.1_rtu.json"},"id":"imaging/rectangular/hst/3e9dd14df5f1c679cb10","identity_limitations":"Isolated to source row: legacy metadata is insufficient for cross-file joins.","instrument":"hst","label":"rectangular \u00b7 hst","model":"rectangular","role":"legacy_or_experimental"},{"configuration":{"image_pixels_masked":{"unit":"count","value":15361},"image_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"linear_gaussians":{"unit":"recorded","value":0},"mask_radius_arcsec":{"unit":"recorded","value":3.5},"n_vis":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"over_sampled_pixels":{"unit":"recorded","value":17980},"oversampled_pixels":{"unit":"recorded","value":17980},"oversampling":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"dimensionless","value":null},"pixel_scale_arcsec":{"unit":"recorded","value":0.05},"preloads":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"psf_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"regularization":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"solver":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"source_pixels":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"transformer":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"vmap_batch_size":{"unit":"recorded","value":3}},"configuration_id":"b507dea06deef9a3d4a6","dataset":"imaging","evidence":{"fragment":null,"path":"results/runtime/imaging/mge/hst/mge_local_cpu_fp64.json"},"id":"imaging/mge/hst/b507dea06deef9a3d4a6","identity_limitations":"Isolated to source row: legacy metadata is insufficient for cross-file joins.","instrument":"hst","label":"mge \u00b7 hst","model":"mge","role":"legacy_or_experimental"},{"configuration":{"image_pixels_masked":{"unit":"count","value":15361},"image_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"linear_gaussians":{"unit":"recorded","value":0},"mask_radius_arcsec":{"unit":"recorded","value":3.5},"n_vis":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"over_sampled_pixels":{"unit":"recorded","value":17980},"oversampled_pixels":{"unit":"recorded","value":17980},"oversampling":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"dimensionless","value":null},"pixel_scale_arcsec":{"unit":"recorded","value":0.05},"preloads":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"psf_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"regularization":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"solver":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"source_pixels":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"transformer":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"vmap_batch_size":{"unit":"recorded","value":3}},"configuration_id":"c013d586e4b27188c85a","dataset":"imaging","evidence":{"fragment":null,"path":"results/runtime/imaging/mge/hst/mge_local_cpu_fp64_sparse.json"},"id":"imaging/mge/hst/c013d586e4b27188c85a","identity_limitations":"Isolated to source row: legacy metadata is insufficient for cross-file joins.","instrument":"hst","label":"mge \u00b7 hst","model":"mge","role":"legacy_or_experimental"},{"configuration":{"batch_size":{"unit":"recorded","value":4},"image_pixels_masked":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"image_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"mixed_precision":{"unit":"recorded","value":false},"n_batch":{"unit":"recorded","value":16},"n_vis":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"ndim":{"unit":"recorded","value":15},"oversampling":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"dimensionless","value":null},"preloads":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"psf_shape":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"pixel","value":null},"regularization":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"solver":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null},"source_pixels":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"count","value":null},"transform":{"unit":"recorded","value":"jit"},"transformer":{"reason":"Not recorded in this legacy evidence; no current default substituted.","unit":"name","value":null}},"configuration_id":"b96665c290af9cb918c0","dataset":"imaging","evidence":{"fragment":"/0","path":"scripts/misc/jax_compile/results/local_cpu/mge.json"},"id":"imaging/mge/hst/b96665c290af9cb918c0","identity_limitations":"Isolated to source row: legacy metadata is insufficient for cross-file joins.","instrument":"hst","label":"mge \u00b7 hst","model":"mge","role":"legacy_or_experimental"}],"unbound_findings":[{"description":"The conversion maps every magnitude at or above 0.999 to q=0.000500250125062532. NumPy reaches the thin valid annulus below one but its constructor guard blocks the beyond-unit region; JAX arrays and tracers bypass that concrete-scalar guard.","discovery":{"models":[],"reason":"Shared component or matrix study. Model usage and exact setup/version applicability have not been established.","shared":true},"evidence":{"fragment":"/findings/component.ell_comps.magnitude-saturation","path":"results/hazards/hazards_index.json"},"id":"component.ell_comps.magnitude-saturation","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"component","subject_name":"ell_comps","title":"ell_comps magnitude saturates at 0.999"},{"description":"A second, load-bearing saturation prevents the q=1 divisions in the elliptical Isothermal deflection from becoming 0/0. Its affected ell_comps disk is too small for prior-sampling discovery.","discovery":{"models":[],"reason":"Shared component or matrix study. Model usage and exact setup/version applicability have not been established.","shared":true},"evidence":{"fragment":"/findings/component.isothermal.near-spherical-saturation","path":"results/hazards/hazards_index.json"},"id":"component.isothermal.near-spherical-saturation","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"component","subject_name":"isothermal","title":"Isothermal caps near-spherical axis ratios at 0.99999"},{"description":"`_wofz_rational` selects one of three rational branches with `xp.where` on |z|^2 and Im(z)^2. The value is continuous to ~1e-6 across a seam but the derivative is not, so `jax.grad` of any MGE deflection carries a kink wherever a grid point crosses a boundary. Autodiff derivative error just above the r2=2.5 seam reaches 7.71e-06 relative, against 1.3e-14 for the SciPy path the numpy backend uses.","discovery":{"models":[],"reason":"Shared MGE mass-profile deflection component study, not specifically the imaging MGE light-model likelihood. Consult the recorded component and revision before applying this finding.","shared":true},"evidence":{"fragment":"/findings/component.mge.faddeeva-seam-gradient","path":"results/hazards/hazards_index.json"},"id":"component.mge.faddeeva-seam-gradient","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"component","subject_name":"mge","title":"The JAX Faddeeva routine's region seams make its derivative discontinuous"},{"description":"The elliptical Faddeeva form is singular at q = 1, so the MGE machinery clamps the axis ratio to 0.9999. The numpy path escapes through an exact radial branch; the JAX path cannot, and every *Sph MGE-routed profile is biased by up to 6.18e-05 relative with a spurious cross-axis deflection of 0.000139 arcsec.","discovery":{"models":[],"reason":"Shared MGE mass-profile deflection component study, not specifically the imaging MGE light-model likelihood. Consult the recorded component and revision before applying this finding.","shared":true},"evidence":{"fragment":"/findings/component.mge.spherical-clamp-bias","path":"results/hazards/hazards_index.json"},"id":"component.mge.spherical-clamp-bias","reason":"Legacy finding does not identify measured library versions and an exact profiling setup; no global applicability inferred.","status":"applicability_unknown","subject":"component","subject_name":"mge","title":"Spherical MGE profiles are evaluated as ellipses at the q = 0.9999 clamp on JAX"},{"description":"The JAX backend replaces the exact SciPy hyp2f1 angular factor with a fixed 20-term omega series. Relative deflection error grows continuously to 0.297 over the measured factor curve.","discovery":{"models":[],"reason":"Shared component or matrix study. 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no current default substituted.\",\"repetitions\":\"Not recorded in this legacy evidence; no current default substituted.\",\"statistic\":\"Not recorded in this legacy evidence; no current default substituted.\",\"synchronization\":\"Not recorded in this legacy evidence; no current default substituted.\",\"warmup\":\"Not recorded in this legacy evidence; no current default substituted.\"},\"warmup\":null},\"metric\":\"c_s3_positive_negative_vmap16.steady_per_call_s\",\"provenance\":{\"has_provenance\":false,\"host\":\"euclid-ral-gpu-2\",\"measured_at\":null,\"qualified\":false,\"unknowns\":{\"measured_at\":\"Not recorded in this legacy evidence; no current default substituted.\"}},\"run_id\":\"legacy/ab7206345ba63a2f46a9\",\"setup_id\":\"imaging/rectangular/hst/b9c3a1e9ced12e87ea7c\",\"unit\":\"s\",\"validation\":{\"reason\":\"Legacy evidence transcribed without scientific baseline acceptance.\",\"status\":\"unreviewed\"}},{\"adapter\":\"profile\",\"axis\":\"compile\",\"evidence\":{\"fragment\":\"/jit_phases/d_s3_certified_fallback_vmap16/first_call_s\",\"path\":\"results/breakdown/imaging/fixed_light_library_rectangular_hpc_a100_fp64_fixed_light_library.json\"},\"id\":\"measurement/0e958cd3eb532f841609\",\"identity\":{\"backend\":\"gpu\",\"device\":\"a100\",\"hardware_details\":{\"autotune_cache_entries_at_start\":0,\"backend\":\"gpu\",\"cache_fresh\":true,\"cpu_count\":124,\"device\":\"cuda:0\",\"hostname\":\"euclid-ral-gpu-2\",\"nvidia_smi\":\"NVIDIA A100 80GB PCIe, 35461 MiB, 81920 MiB\",\"omp_num_threads\":null,\"xla_flags\":\"--xla_disable_hlo_passes=constant_folding --xla_gpu_autotune_level=0 --xla_gpu_enable_triton_gemm=false\"},\"library_version\":\"2026.8.17.1\",\"precision\":\"float64\",\"software\":{\"PyAutoLens\":\"2026.8.17.1\"},\"unknowns\":{}},\"measurement\":{\"d_s3_certified_fallback_vmap16.first_call_s\":5.4974286472424865},\"method\":{\"cache_state\":null,\"id\":\"legacy/f6f64cb23ad74fe67fc7\",\"repetitions\":null,\"statistic\":null,\"synchronization\":null,\"unknowns\":{\"cache_state\":\"Not recorded in this legacy evidence; no current default substituted.\",\"repetitions\":\"Not recorded in this legacy evidence; no current default substituted.\",\"statistic\":\"Not recorded in this legacy evidence; no current default substituted.\",\"synchronization\":\"Not recorded in this legacy evidence; no current default substituted.\",\"warmup\":\"Not recorded in this legacy evidence; no current default substituted.\"},\"warmup\":null},\"metric\":\"d_s3_certified_fallback_vmap16.first_call_s\",\"provenance\":{\"has_provenance\":false,\"host\":\"euclid-ral-gpu-2\",\"measured_at\":null,\"qualified\":false,\"unknowns\":{\"measured_at\":\"Not recorded in this legacy evidence; no current default substituted.\"}},\"run_id\":\"legacy/ab7206345ba63a2f46a9\",\"setup_id\":\"imaging/rectangular/hst/b9c3a1e9ced12e87ea7c\",\"unit\":\"s\",\"validation\":{\"reason\":\"Legacy evidence transcribed without scientific baseline acceptance.\",\"status\":\"unreviewed\"}},{\"adapter\":\"profile\",\"axis\":\"breakdown\",\"evidence\":{\"fragment\":\"/jit_phases/d_s3_certified_fallback_vmap16/steady_per_call_s\",\"path\":\"results/breakdown/imaging/fixed_light_library_rectangular_hpc_a100_fp64_fixed_light_library.json\"},\"id\":\"measurement/420551f3e9fd5b0b934d\",\"identity\":{\"backend\":\"gpu\",\"device\":\"a100\",\"hardware_details\":{\"autotune_cache_entries_at_start\":0,\"backend\":\"gpu\",\"cache_fresh\":true,\"cpu_count\":124,\"device\":\"cuda:0\",\"hostname\":\"euclid-ral-gpu-2\",\"nvidia_smi\":\"NVIDIA A100 80GB PCIe, 35461 MiB, 81920 MiB\",\"omp_num_threads\":null,\"xla_flags\":\"--xla_disable_hlo_passes=constant_folding --xla_gpu_autotune_level=0 --xla_gpu_enable_triton_gemm=false\"},\"library_version\":\"2026.8.17.1\",\"precision\":\"float64\",\"software\":{\"PyAutoLens\":\"2026.8.17.1\"},\"unknowns\":{}},\"measurement\":{\"d_s3_certified_fallback_vmap16.steady_per_call_s\":0.03384811292635277},\"method\":{\"cache_state\":null,\"id\":\"legacy/2856ec9b81be8df25b2d\",\"repetitions\":null,\"statistic\":null,\"synchronization\":null,\"unknowns\":{\"cache_state\":\"Not recorded in this legacy evidence; no current default substituted.\",\"repetitions\":\"Not recorded in this legacy evidence; no current default substituted.\",\"statistic\":\"Not recorded in this legacy evidence; no current default substituted.\",\"synchronization\":\"Not recorded in this legacy evidence; no current default substituted.\",\"warmup\":\"Not recorded in this legacy evidence; no current default substituted.\"},\"warmup\":null},\"metric\":\"d_s3_certified_fallback_vmap16.steady_per_call_s\",\"provenance\":{\"has_provenance\":false,\"host\":\"euclid-ral-gpu-2\",\"measured_at\":null,\"qualified\":false,\"unknowns\":{\"measured_at\":\"Not recorded in this legacy evidence; no current default substituted.\"}},\"run_id\":\"legacy/ab7206345ba63a2f46a9\",\"setup_id\":\"imaging/rectangular/hst/b9c3a1e9ced12e87ea7c\",\"unit\":\"s\",\"validation\":{\"reason\":\"Legacy evidence transcribed without scientific baseline acceptance.\",\"status\":\"unreviewed\"}},{\"adapter\":\"profile\",\"axis\":\"compile\",\"evidence\":{\"fragment\":\"/jit_phases/d0_s3_certified_no_fallback_vmap16/first_call_s\",\"path\":\"results/breakdown/imaging/fixed_light_library_rectangular_hpc_a100_fp64_fixed_light_library.json\"},\"id\":\"measurement/6a723300a59f0c8898b3\",\"identity\":{\"backend\":\"gpu\",\"device\":\"a100\",\"hardware_details\":{\"autotune_cache_entries_at_start\":0,\"backend\":\"gpu\",\"cache_fresh\":true,\"cpu_count\":124,\"device\":\"cuda:0\",\"hostname\":\"euclid-ral-gpu-2\",\"nvidia_smi\":\"NVIDIA A100 80GB PCIe, 35461 MiB, 81920 MiB\",\"omp_num_threads\":null,\"xla_flags\":\"--xla_disable_hlo_passes=constant_folding --xla_gpu_autotune_level=0 --xla_gpu_enable_triton_gemm=false\"},\"library_version\":\"2026.8.17.1\",\"precision\":\"float64\",\"software\":{\"PyAutoLens\":\"2026.8.17.1\"},\"unknowns\":{}},\"measurement\":{\"d0_s3_certified_no_fallback_vmap16.first_call_s\":6.334332124795765},\"method\":{\"cache_state\":null,\"id\":\"legacy/e8f6ace5329908f1a427\",\"repetitions\":null,\"statistic\":null,\"synchronization\":null,\"unknowns\":{\"cache_state\":\"Not recorded in this legacy evidence; no current default substituted.\",\"repetitions\":\"Not recorded in this legacy evidence; no current default substituted.\",\"statistic\":\"Not recorded in this legacy evidence; no current default substituted.\",\"synchronization\":\"Not recorded in this legacy evidence; no current default substituted.\",\"warmup\":\"Not recorded in this legacy evidence; no current default substituted.\"},\"warmup\":null},\"metric\":\"d0_s3_certified_no_fallback_vmap16.first_call_s\",\"provenance\":{\"has_provenance\":false,\"host\":\"euclid-ral-gpu-2\",\"measured_at\":null,\"qualified\":false,\"unknowns\":{\"measured_at\":\"Not recorded in this legacy evidence; no current default substituted.\"}},\"run_id\":\"legacy/ab7206345ba63a2f46a9\",\"setup_id\":\"imaging/rectangular/hst/b9c3a1e9ced12e87ea7c\",\"unit\":\"s\",\"validation\":{\"reason\":\"Legacy evidence transcribed without scientific baseline acceptance.\",\"status\":\"unreviewed\"}},{\"adapter\":\"profile\",\"axis\":\"breakdown\",\"evidence\":{\"fragment\":\"/jit_phases/d0_s3_certified_no_fallback_vmap16/steady_per_call_s\",\"path\":\"results/breakdown/imaging/fixed_light_library_rectangular_hpc_a100_fp64_fixed_light_library.json\"},\"id\":\"measurement/81a9bb0c0dbb7486b932\",\"identity\":{\"backend\":\"gpu\",\"device\":\"a100\",\"hardware_details\":{\"autotune_cache_entries_at_start\":0,\"backend\":\"gpu\",\"cache_fresh\":true,\"cpu_count\":124,\"device\":\"cuda:0\",\"hostname\":\"euclid-ral-gpu-2\",\"nvidia_smi\":\"NVIDIA A100 80GB PCIe, 35461 MiB, 81920 MiB\",\"omp_num_threads\":null,\"xla_flags\":\"--xla_disable_hlo_passes=constant_folding --xla_gpu_autotune_level=0 --xla_gpu_enable_triton_gemm=false\"},\"library_version\":\"2026.8.17.1\",\"precision\":\"float64\",\"software\":{\"PyAutoLens\":\"2026.8.17.1\"},\"unknowns\":{}},\"measurement\":{\"d0_s3_certified_no_fallback_vmap16.steady_per_call_s\":0.021351748943561687},\"method\":{\"cache_state\":null,\"id\":\"legacy/97bc25e6f7eef79c43fe\",\"repetitions\":null,\"statistic\":null,\"synchronization\":null,\"unknowns\":{\"cache_state\":\"Not recorded in this legacy evidence; no current default substituted.\",\"repetitions\":\"Not recorded in this legacy evidence; no current default substituted.\",\"statistic\":\"Not recorded in this legacy evidence; no current default substituted.\",\"synchronization\":\"Not recorded in this legacy evidence; no current default substituted.\",\"warmup\":\"Not recorded in this legacy evidence; no current default substituted.\"},\"warmup\":null},\"metric\":\"d0_s3_certified_no_fallback_vmap16.steady_per_call_s\",\"provenance\":{\"has_provenance\":false,\"host\":\"euclid-ral-gpu-2\",\"measured_at\":null,\"qualified\":false,\"unknowns\":{\"measured_at\":\"Not recorded in this legacy evidence; no current default substituted.\"}},\"run_id\":\"legacy/ab7206345ba63a2f46a9\",\"setup_id\":\"imaging/rectangular/hst/b9c3a1e9ced12e87ea7c\",\"unit\":\"s\",\"validation\":{\"reason\":\"Legacy evidence transcribed without scientific baseline acceptance.\",\"status\":\"unreviewed\"}},{\"adapter\":\"profile\",\"axis\":\"compile\",\"evidence\":{\"fragment\":\"/jit_phases/e_s3_certified_budget1_fallback_fires_vmap16/first_call_s\",\"path\":\"results/breakdown/imaging/fixed_light_library_rectangular_hpc_a100_fp64_fixed_light_library.json\"},\"id\":\"measurement/ecd90afeb3f9f1bfde57\",\"identity\":{\"backend\":\"gpu\",\"device\":\"a100\",\"hardware_details\":{\"autotune_cache_entries_at_start\":0,\"backend\":\"gpu\",\"cache_fresh\":true,\"cpu_count\":124,\"device\":\"cuda:0\",\"hostname\":\"euclid-ral-gpu-2\",\"nvidia_smi\":\"NVIDIA A100 80GB PCIe, 35461 MiB, 81920 MiB\",\"omp_num_threads\":null,\"xla_flags\":\"--xla_disable_hlo_passes=constant_folding --xla_gpu_autotune_level=0 --xla_gpu_enable_triton_gemm=false\"},\"library_version\":\"2026.8.17.1\",\"precision\":\"float64\",\"software\":{\"PyAutoLens\":\"2026.8.17.1\"},\"unknowns\":{}},\"measurement\":{\"e_s3_certified_budget1_fallback_fires_vmap16.first_call_s\":7.976106060203165},\"method\":{\"cache_state\":null,\"id\":\"legacy/546c989e8f2c53d44b20\",\"repetitions\":null,\"statistic\":null,\"synchronization\":null,\"unknowns\":{\"cache_state\":\"Not recorded in this legacy evidence; no current default substituted.\",\"repetitions\":\"Not recorded in this legacy evidence; no current default substituted.\",\"statistic\":\"Not recorded in this legacy evidence; no current default substituted.\",\"synchronization\":\"Not recorded in this legacy evidence; no current default substituted.\",\"warmup\":\"Not recorded in this legacy evidence; no current default substituted.\"},\"warmup\":null},\"metric\":\"e_s3_certified_budget1_fallback_fires_vmap16.first_call_s\",\"provenance\":{\"has_provenance\":false,\"host\":\"euclid-ral-gpu-2\",\"measured_at\":null,\"qualified\":false,\"unknowns\":{\"measured_at\":\"Not recorded in this legacy evidence; no current default substituted.\"}},\"run_id\":\"legacy/ab7206345ba63a2f46a9\",\"setup_id\":\"imaging/rectangular/hst/b9c3a1e9ced12e87ea7c\",\"unit\":\"s\",\"validation\":{\"reason\":\"Legacy evidence transcribed without scientific baseline acceptance.\",\"status\":\"unreviewed\"}},{\"adapter\":\"profile\",\"axis\":\"breakdown\",\"evidence\":{\"fragment\":\"/jit_phases/e_s3_certified_budget1_fallback_fires_vmap16/steady_per_call_s\",\"path\":\"results/breakdown/imaging/fixed_light_library_rectangular_hpc_a100_fp64_fixed_light_library.json\"},\"id\":\"measurement/03b0cfbed9e5b4d3e378\",\"identity\":{\"backend\":\"gpu\",\"device\":\"a100\",\"hardware_details\":{\"autotune_cache_entries_at_start\":0,\"backend\":\"gpu\",\"cache_fresh\":true,\"cpu_count\":124,\"device\":\"cuda:0\",\"hostname\":\"euclid-ral-gpu-2\",\"nvidia_smi\":\"NVIDIA A100 80GB PCIe, 35461 MiB, 81920 MiB\",\"omp_num_threads\":null,\"xla_flags\":\"--xla_disable_hlo_passes=constant_folding --xla_gpu_autotune_level=0 --xla_gpu_enable_triton_gemm=false\"},\"library_version\":\"2026.8.17.1\",\"precision\":\"float64\",\"software\":{\"PyAutoLens\":\"2026.8.17.1\"},\"unknowns\":{}},\"measurement\":{\"e_s3_certified_budget1_fallback_fires_vmap16.steady_per_call_s\":0.03028988981968723},\"method\":{\"cache_state\":null,\"id\":\"legacy/585348695005a337c293\",\"repetitions\":null,\"statistic\":null,\"synchronization\":null,\"unknowns\":{\"cache_state\":\"Not recorded in this legacy evidence; no current default substituted.\",\"repetitions\":\"Not recorded in this legacy evidence; no current default substituted.\",\"statistic\":\"Not recorded in this legacy evidence; no current default substituted.\",\"synchronization\":\"Not recorded in this legacy evidence; no current default substituted.\",\"warmup\":\"Not recorded in this legacy evidence; no current default substituted.\"},\"warmup\":null},\"metric\":\"e_s3_certified_budget1_fallback_fires_vmap16.steady_per_call_s\",\"provenance\":{\"has_provenance\":false,\"host\":\"euclid-ral-gpu-2\",\"measured_at\":null,\"qualified\":false,\"unknowns\":{\"measured_at\":\"Not recorded in this legacy evidence; no current default substituted.\"}},\"run_id\":\"legacy/ab7206345ba63a2f46a9\",\"setup_id\":\"imaging/rectangular/hst/b9c3a1e9ced12e87ea7c\",\"unit\":\"s\",\"validation\":{\"reason\":\"Legacy evidence transcribed without scientific baseline acceptance.\",\"status\":\"unreviewed\"}}],\"schema\":\"profiling-summary\",\"scope\":\"setup-catalogue\",\"selections\":[],\"setups\":[{\"configuration\":{\"fallback_row_budget\":{\"unit\":\"recorded\",\"value\":1},\"fallback_rows\":{\"unit\":\"recorded\",\"value\":true},\"image_pixels_masked\":{\"unit\":\"count\",\"value\":15361},\"image_shape\":{\"reason\":\"Not recorded in this legacy evidence; no current default substituted.\",\"unit\":\"pixel\",\"value\":null},\"mask_radius_arcsec\":{\"unit\":\"recorded\",\"value\":3.5},\"memo\":{\"unit\":\"recorded\",\"value\":\"library_default (inert on the JAX path)\"},\"mesh\":{\"unit\":\"recorded\",\"value\":\"rectangular\"},\"mesh_shape\":{\"unit\":\"recorded\",\"value\":[39,39]},\"n_vis\":{\"reason\":\"Not recorded in this legacy evidence; no current default substituted.\",\"unit\":\"count\",\"value\":null},\"over_sample_size_lp_rule\":{\"unit\":\"recorded\",\"value\":{\"centre\":[0.0,0.0],\"radial_list\":[0.3,0.6],\"sub_size_list\":[4,2,2]}},\"over_sampled_pixels\":{\"unit\":\"recorded\",\"value\":62752},\"oversampled_pixels\":{\"unit\":\"recorded\",\"value\":62752},\"oversampling\":{\"reason\":\"Not recorded in this legacy evidence; no current default substituted.\",\"unit\":\"dimensionless\",\"value\":null},\"pass_budget\":{\"unit\":\"recorded\",\"value\":7},\"pass_budget_max_diagnostics\":{\"unit\":\"recorded\",\"value\":8},\"pixel_scale_arcsec\":{\"unit\":\"recorded\",\"value\":0.05},\"preloads\":{\"reason\":\"Not recorded in this legacy evidence; no current default substituted.\",\"unit\":\"name\",\"value\":null},\"psf_shape\":{\"reason\":\"Not recorded in this legacy evidence; no current default substituted.\",\"unit\":\"pixel\",\"value\":null},\"rect_mesh\":{\"unit\":\"recorded\",\"value\":\"bilinear\"},\"regularization\":{\"unit\":\"name\",\"value\":{\"coefficient\":1.0,\"scheme\":\"constant\"}},\"solver\":{\"reason\":\"Not recorded in this legacy evidence; no current default substituted.\",\"unit\":\"name\",\"value\":null},\"source_pixels\":{\"unit\":\"count\",\"value\":1521},\"source_pixels_requested\":{\"reason\":\"Not recorded in this legacy evidence; no current default substituted.\",\"unit\":\"recorded\",\"value\":null},\"thread_env\":{\"unit\":\"recorded\",\"value\":{\"n_threads\":null,\"note\":\"Not pinned (legacy variant): recorded as found.\",\"overridden\":{},\"preexisting\":{},\"set_to\":null,\"vars\":[\"OPENBLAS_NUM_THREADS\",\"MKL_NUM_THREADS\",\"OMP_NUM_THREADS\",\"VECLIB_MAXIMUM_THREADS\",\"NUMEXPR_NUM_THREADS\"]}},\"transformer\":{\"reason\":\"Not recorded in this legacy evidence; no current default substituted.\",\"unit\":\"name\",\"value\":null},\"vmap_batch\":{\"unit\":\"recorded\",\"value\":16}},\"configuration_id\":\"b9c3a1e9ced12e87ea7c\",\"dataset\":\"imaging\",\"evidence\":{\"fragment\":null,\"path\":\"results/breakdown/imaging/fixed_light_library_rectangular_hpc_a100_fp64_fixed_light_library.json\"},\"id\":\"imaging/rectangular/hst/b9c3a1e9ced12e87ea7c\",\"identity_limitations\":\"Isolated to source row: legacy metadata is insufficient for cross-file joins.\",\"instrument\":\"hst\",\"label\":\"rectangular \\u00b7 hst\",\"model\":\"rectangular\",\"role\":\"legacy_or_experimental\"}],\"valid_until\":null,\"version\":2}\n"}}
diff --git a/tests/test_setup_browser.py b/tests/test_setup_browser.py
index bec8cad..630a4cc 100644
--- a/tests/test_setup_browser.py
+++ b/tests/test_setup_browser.py
@@ -75,3 +75,23 @@ def test_markdown_keeps_diagnostics_collapsed():
     page = board.render_markdown([capture()])
     assert "<details><summary>Capture, qualification and legacy diagnostics" in page
     assert "| Where | Count |" not in page
+
+
+def test_real_browser_fixture_preserves_capture_hashes_and_setup_identity():
+    import hashlib
+    from pathlib import Path
+
+    from pulse import catalogue
+
+    fixture = json.loads((Path(__file__).parent / "fixtures/browser_measurements.json").read_text())
+    assert len(fixture["capture_commit"]) == 40
+    assert catalogue.validate(fixture["catalogue"]) == []
+    for manifest in fixture["catalogue"]["evidence_shards"]:
+        raw = fixture["shards"][manifest["path"]]
+        assert hashlib.sha256(raw.encode()).hexdigest() == manifest["sha256"]
+        shard = json.loads(raw)
+        assert catalogue.validate(shard) == []
+        assert len(shard["records"]) == manifest["records"]
+        assert shard["setups"] == [
+            setup for setup in fixture["catalogue"]["setups"] if setup["id"] == manifest["setup_id"]
+        ]