From 2bdfabb9413df314cfb7cbcabe335c01d904d404 Mon Sep 17 00:00:00 2001
From: Jammy2211 <JNightingale2211@gmail.com>
Date: Thu, 15 Oct 2026 16:23:20 +0100
Subject: [PATCH 1/2] =?UTF-8?q?cortex:=20autofit=5Finference=20=E2=80=94?=
 =?UTF-8?q?=20scored=20wave=202=20pulled=20and=20judged=20under=20gaussian?=
 =?UTF-8?q?=5Fx3@2;=20probe-first=20remainder=20on=20ral=20(B5b)?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Moves 408244-408367 into the log with walls (sacct: all 1,629 tasks COMPLETED), opens
409930 (980-run probe-first remainder), rewrites Now; dashboard rendered with --cortex
on this worktree.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 dashboard.html                | 32 ++++++++++++--------------------
 dashboard.md                  | 32 ++++++++++++--------------------
 projects/autofit_inference.md | 22 ++++++++++++----------
 state.json                    |  4 ++--
 4 files changed, 38 insertions(+), 52 deletions(-)

diff --git a/dashboard.html b/dashboard.html
index 7c301ad..9268b8c 100644
--- a/dashboard.html
+++ b/dashboard.html
@@ -4,7 +4,7 @@
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1">
 <title>PyAutoCortex Dashboard</title>
-<!-- generated by `pyauto-brain cortex dashboard --apply` on 2026-10-14 — regenerate, do not hand-edit -->
+<!-- generated by `pyauto-brain cortex dashboard --apply` on 2026-10-15 — regenerate, do not hand-edit -->
 <style>:root{color-scheme:light dark;--bg:#fff;--fg:#1f2328;--muted:#59636e;
  --board-max:77.5rem;--board-gutter:1rem;--board-measure:65ch;
  --line:#d8dee4;--btn:#f6f8fa;--ok:#1a7f37;--warn:#9a6700;--bad:#d1242f;
@@ -331,11 +331,11 @@
 - Open slope_hierarchy_scale: https://github.com/PyAutoLabs/slope_hierarchy_scale
 - Open ic50_workspace: https://github.com/Jammy2211/ic50_workspace
 - Open autolens_inference: https://github.com/PyAutoLabs/autolens_inference
-- Open autofit_inference: https://github.com/PyAutoLabs/autofit_inference</textarea></details><div class="orchestration-freshness" data-freshness="grey"><details data-freshness-stamp data-refreshed-at="2026-10-14T16:20:56Z"><summary><span data-freshness-label>Last updated 2026-10-14 16:20:56 UTC</span></summary><time datetime="2026-10-14T16:20:56Z">2026-10-14 16:20:56 UTC</time></details><a data-refresh-link href="https://github.com/PyAutoLabs/PyAutoCortex/actions/workflows/dashboard_refresh.yml" title="Open the dashboard refresh controls">↻ Update</a></div></div><p class="orchestration-status" role="status" aria-live="polite"></p></section>
-<nav class="board-nav" aria-label="Board sections"><a class="board-nav-card" href="#summary"><span class="board-nav-count">25</span><span class="board-nav-label">Running</span></a><a class="board-nav-card" href="#summary"><span class="board-nav-count">53</span><span class="board-nav-label">Open</span></a><a class="board-nav-card" href="#projects"><span class="board-nav-count">8</span><span class="board-nav-label">Projects</span></a><a class="board-nav-card" href="#orchestration-cortex"><span class="board-nav-label">Check in</span></a></nav>
+- Open autofit_inference: https://github.com/PyAutoLabs/autofit_inference</textarea></details><div class="orchestration-freshness" data-freshness="grey"><details data-freshness-stamp data-refreshed-at="2026-10-15T15:22:54Z"><summary><span data-freshness-label>Last updated 2026-10-15 15:22:54 UTC</span></summary><time datetime="2026-10-15T15:22:54Z">2026-10-15 15:22:54 UTC</time></details><a data-refresh-link href="https://github.com/PyAutoLabs/PyAutoCortex/actions/workflows/dashboard_refresh.yml" title="Open the dashboard refresh controls">↻ Update</a></div></div><p class="orchestration-status" role="status" aria-live="polite"></p></section>
+<nav class="board-nav" aria-label="Board sections"><a class="board-nav-card" href="#summary"><span class="board-nav-count">22</span><span class="board-nav-label">Running</span></a><a class="board-nav-card" href="#summary"><span class="board-nav-count">48</span><span class="board-nav-label">Open</span></a><a class="board-nav-card" href="#projects"><span class="board-nav-count">8</span><span class="board-nav-label">Projects</span></a><a class="board-nav-card" href="#orchestration-cortex"><span class="board-nav-label">Check in</span></a></nav>
 
 <p class="muted mdsrc"><a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/dashboard.md" class="board-source-link" title="Markdown version" aria-label="Markdown version"><svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.6" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true" focusable="false"><path d="M14 3H6a1 1 0 0 0-1 1v16a1 1 0 0 0 1 1h12a1 1 0 0 0 1-1V8Z"/><path d="M14 3v5h5M8 12h8M8 16h6"/></svg></a></p>
-<details class="board-section"><summary><h2>Summary</h2><span class="section-badge">25 Running · 53 Open</span></summary><div class="board-section-body"><a id="summary"></a>
+<details class="board-section"><summary><h2>Summary</h2><span class="section-badge">22 Running · 48 Open</span></summary><div class="board-section-body"><a id="summary"></a>
 <table class="map">
 <tr><th>Project</th><th>Running</th><th>Open</th><th>Last update</th></tr>
 <tr><td><b>subhalo_validation</b></td><td>0</td><td>5</td><td>2026-09-07</td></tr>
@@ -345,7 +345,7 @@
 <tr><td><b>slope_hierarchy_scale</b></td><td>0</td><td>0</td><td>2026-10-14</td></tr>
 <tr><td><b>ic50_workspace</b></td><td>0</td><td>0</td><td>2026-10-14</td></tr>
 <tr><td><b>autolens_inference</b></td><td>6</td><td>0</td><td>2026-09-24</td></tr>
-<tr><td><b>autofit_inference</b></td><td>3</td><td>6</td><td>2026-10-14</td></tr>
+<tr><td><b>autofit_inference</b></td><td>0</td><td>1</td><td>2026-10-15</td></tr>
 </table>
 </div></details><details class="board-section"><summary><h2>Projects</h2><span class="section-badge">8</span></summary><div class="board-section-body"><a id="projects"></a>
 <section class="project">
@@ -550,26 +550,18 @@ <h3>autolens_inference — Do the PyAutoLens inference backends agree on the HST
 <h3>autofit_inference — PyAutoFit search benchmark on gaussian_x3: which searches find the right answer fastest</h3>
 <p class="muted">active · ral · <a href="https://github.com/PyAutoLabs/autofit_inference/issues/8">autofit_inference#8</a> · <a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/autofit_inference.md">projects/autofit_inference.md</a> · local <span class="pathchip">/home/jammy/Code/PyAutoLabs/fit/autofit_inference</span> · RAL <span class="pathchip">/mnt/ral/jnightin/autofit_inference</span></p>
 <p><b>Now</b></p>
-<p>gaussian_x3@2 frozen in autofit_inference 72d6faaf1717 before any scored run (A2+A4 gate met: PyAutoFit df6d218f1). Scored wave 2 submitted 2026-10-14 on RAL ral (11,750 runs + 20-run probe; references first) against a private PyAutoFit pin df6d218f10cd (autofit_inference#9). Next: B5b pulls, builds the JAX blend realisation-1 reference on the laptop, judges under @2.</p>
+<p>Scored wave 2 pulled and judged under gaussian_x3@2 (B5b, 2026-10-15): 11,770 rows at PyAutoFit pin df6d218f10cd all admitted; accounting 11,750 scored (10,580 rows, 1,170 failed) + 20 probe + 250 deferred; all 20 per-realisation references complete (Nautilus-only), JAX blend realisation-1 rebuilt locally. Catalogue gaussian_x3@2 section orders legs within task and dataset (autofit_inference results/accounting, catalogue). Probe-first remainder (980 runs) is 409930 on ral; next: B5b-2 pulls and judges it; wave-2 summary records withheld on size pending autofit_inference#10.</p>
 <p><b>Runs</b></p>
 <ul>
-<li>408244_[0-49] — running — ral — 2026-10-14 — wave-2 blend references (gaussian_x3@2 freeze 72d6faaf1717): realisations 2-5 x numpy/jax x Nautilus n_live=2000 + DynestyStatic nlive=1000 seeds 0-2, + JAX Na…</li>
-<li>408245_[0-47] — running — ral — 2026-10-14 — wave-2 separated references: realisations 1,3,4,5 x numpy/jax x 6 runs; %48; submit_wave2_reference_gaussian_x3_separated; pin df6d218f10cd</li>
-<li>408246_[0-19] — running — ral — 2026-10-14 — wave-2 probe: Zeus JAX + NSS n_live_200_mcmc_steps_50, both datasets, realisation 1, seeds 0-4 (timeouts for probe-first cells); %20; submit_wave2_probe</li>
-<li>408346_[0-7] — open — ral — 2026-10-14 — wave-2 blend reference builds (MAP + build_reference), afterany 408244; %8</li>
-<li>408347_[0-7] — open — ral — 2026-10-14 — wave-2 separated reference builds, afterany 408245; %8</li>
-<li>408348_[0-379] — open — ral — 2026-10-14 — scored wave 2 (gaussian_x3@2) blend numpy: 2250 runs, 50 seeds x 5 realisations, %60, afterany 408346:408347; submit_wave2_scored_gaussian_x3_blend_numpy</li>
-<li>408365_[0-344] — open — ral — 2026-10-14 — scored wave 2 blend jax_cpu: 3500 runs, %60, afterany 408346:408347</li>
-<li>408366_[0-379] — open — ral — 2026-10-14 — scored wave 2 separated numpy: 2250 runs, %60, afterany 408346:408347</li>
-<li>408367_[0-389] — open — ral — 2026-10-14 — scored wave 2 separated jax_cpu: 3750 runs, %60, afterany 408346:408347</li>
+<li>409930_[0-19] — open — ral — 2026-10-15 — wave-2 probe-first remainder (B5b): Zeus JAX + NSS n_live_200_mcmc_steps_50, both datasets, 980 runs after the probe under probe-derived @2 timeouts (NSS 600 s…</li>
 </ul>
 <p><b>Last 5</b></p>
 <ul>
-<li>2026-10-14 — <i>note</i> — gaussian_x3@2 frozen (autofit_inference 72d6faaf1717, protocol 11 A2) before any scored run; A4 gate met (PyAutoFit df6d218f1). Dry run 408236 on ral: pin imports, RAL 4-7x faster than the laptop pilot (laptop-derived timeouts are lenient)…</li>
-<li>2026-10-14 — <i>run</i> — 408367_[0-389] submitted: scored wave 2 separated jax_cpu: 3750 runs, %60, afterany 408346:408347</li>
-<li>2026-10-14 — <i>run</i> — 408366_[0-379] submitted: scored wave 2 separated numpy: 2250 runs, %60, afterany 408346:408347</li>
-<li>2026-10-14 — <i>run</i> — 408365_[0-344] submitted: scored wave 2 blend jax_cpu: 3500 runs, %60, afterany 408346:408347</li>
-<li>2026-10-14 — <i>run</i> — 408348_[0-379] submitted: scored wave 2 (gaussian_x3@2) blend numpy: 2250 runs, 50 seeds x 5 realisations, %60, afterany 408346:408347; submit_wave2_scored_gaussian_x3_blend_numpy</li>
+<li>2026-10-15 — <i>run</i> — 408367_[0-389] finished — wall 1:57: scored wave 2 separated jax_cpu: 3750 runs, %60, afterany 408346:408347 — 390/390 COMPLETED; 3750 separated jax_cpu rows admitted; judged B5b</li>
+<li>2026-10-15 — <i>run</i> — 408366_[0-379] finished — wall 1:51: scored wave 2 separated numpy: 2250 runs, %60, afterany 408346:408347 — 380/380 COMPLETED; 2250 separated numpy rows admitted; judged B5b</li>
+<li>2026-10-15 — <i>run</i> — 408365_[0-344] finished — wall 1:46: scored wave 2 blend jax_cpu: 3500 runs, %60, afterany 408346:408347 — 345/345 COMPLETED; 3500 blend jax_cpu rows admitted; judged B5b</li>
+<li>2026-10-15 — <i>run</i> — 408348_[0-379] finished — wall 1:53: scored wave 2 (gaussian_x3@2) blend numpy: 2250 runs, 50 seeds x 5 realisations, %60, afterany 408346:408347; submit_wave2_scored_gaussian_x3_blend_numpy — 380/380 COMPLETED; 2250 blend numpy rows admit…</li>
+<li>2026-10-15 — <i>run</i> — 408347_[0-7] finished — wall 0:01: wave-2 separated reference builds, afterany 408245; %8 — 8/8 COMPLETED; separated reference builds</li>
 </ul>
 <p class="muted"><a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/autofit_inference.md">full log</a></p>
 <div class="task"><button class="copy" data-cmd="Use the cortex skill. — resume autofit_inference: read PyAutoCortex projects/autofit_inference.md (Now, Runs, Log) and then /home/jammy/Code/PyAutoLabs/fit/autofit_inference/wiki/project/state.md and the assistant autofit_assistant's AGENTS.md; tell me where I left off and what I said I would do next. Submit nothing and log nothing until I say." aria-label="Copy the AI command">📋</button><p>resume autofit_inference</p></div>
diff --git a/dashboard.md b/dashboard.md
index b8d4b0e..86c94f6 100644
--- a/dashboard.md
+++ b/dashboard.md
@@ -1,17 +1,17 @@
 # PyAutoCortex Dashboard
 
-<!-- generated by `pyauto-brain cortex dashboard --apply` on 2026-10-14 — regenerate, do not hand-edit -->
+<!-- generated by `pyauto-brain cortex dashboard --apply` on 2026-10-15 — regenerate, do not hand-edit -->
 
 This is the markdown version of the [PyAutoCortex Dashboard](https://pyautolabs.github.io/PyAutoCortex/), which puts the check-in and each project's resume prompt on your clipboard with a single tap of 📋.
 
 One ledger per science project: what is on the cluster right now, what the human said they would do next, and the last few things they wrote down. Nothing here is inferred from a result — the board hands you the check-in and the resume prompt; what a run meant is yours to log.
 
-> **Last updated 2026-10-14.**
+> **Last updated 2026-10-15.**
 
 | Where | Count |
 |-------|------:|
-| [Running](#projects) | 25 |
-| [Open](#projects) | 53 |
+| [Running](#projects) | 22 |
+| [Open](#projects) | 48 |
 | [Projects](#projects) | 8 |
 
 <details><summary>📋 check in since last time</summary>
@@ -49,7 +49,7 @@ Last check-in: 2026-09-30T09:51Z.
 | slope_hierarchy_scale | 0 | 0 | 2026-10-14 |
 | ic50_workspace | 0 | 0 | 2026-10-14 |
 | autolens_inference | 6 | 0 | 2026-09-24 |
-| autofit_inference | 3 | 6 | 2026-10-14 |
+| autofit_inference | 0 | 1 | 2026-10-15 |
 
 ## Projects
 
@@ -336,27 +336,19 @@ active · ral · [autofit_inference#8](https://github.com/PyAutoLabs/autofit_inf
 
 **Now**
 
-gaussian_x3@2 frozen in autofit_inference 72d6faaf1717 before any scored run (A2+A4 gate met: PyAutoFit df6d218f1). Scored wave 2 submitted 2026-10-14 on RAL ral (11,750 runs + 20-run probe; references first) against a private PyAutoFit pin df6d218f10cd (autofit_inference#9). Next: B5b pulls, builds the JAX blend realisation-1 reference on the laptop, judges under @2.
+Scored wave 2 pulled and judged under gaussian_x3@2 (B5b, 2026-10-15): 11,770 rows at PyAutoFit pin df6d218f10cd all admitted; accounting 11,750 scored (10,580 rows, 1,170 failed) + 20 probe + 250 deferred; all 20 per-realisation references complete (Nautilus-only), JAX blend realisation-1 rebuilt locally. Catalogue gaussian_x3@2 section orders legs within task and dataset (autofit_inference results/accounting, catalogue). Probe-first remainder (980 runs) is 409930 on ral; next: B5b-2 pulls and judges it; wave-2 summary records withheld on size pending autofit_inference#10.
 
 **Runs**
 
-- 408244_[0-49] — running — ral — 2026-10-14 — wave-2 blend references (gaussian_x3@2 freeze 72d6faaf1717): realisations 2-5 x numpy/jax x Nautilus n_live=2000 + DynestyStatic nlive=1000 seeds 0-2, + JAX Na…
-- 408245_[0-47] — running — ral — 2026-10-14 — wave-2 separated references: realisations 1,3,4,5 x numpy/jax x 6 runs; %48; submit_wave2_reference_gaussian_x3_separated; pin df6d218f10cd
-- 408246_[0-19] — running — ral — 2026-10-14 — wave-2 probe: Zeus JAX + NSS n_live_200_mcmc_steps_50, both datasets, realisation 1, seeds 0-4 (timeouts for probe-first cells); %20; submit_wave2_probe
-- 408346_[0-7] — open — ral — 2026-10-14 — wave-2 blend reference builds (MAP + build_reference), afterany 408244; %8
-- 408347_[0-7] — open — ral — 2026-10-14 — wave-2 separated reference builds, afterany 408245; %8
-- 408348_[0-379] — open — ral — 2026-10-14 — scored wave 2 (gaussian_x3@2) blend numpy: 2250 runs, 50 seeds x 5 realisations, %60, afterany 408346:408347; submit_wave2_scored_gaussian_x3_blend_numpy
-- 408365_[0-344] — open — ral — 2026-10-14 — scored wave 2 blend jax_cpu: 3500 runs, %60, afterany 408346:408347
-- 408366_[0-379] — open — ral — 2026-10-14 — scored wave 2 separated numpy: 2250 runs, %60, afterany 408346:408347
-- 408367_[0-389] — open — ral — 2026-10-14 — scored wave 2 separated jax_cpu: 3750 runs, %60, afterany 408346:408347
+- 409930_[0-19] — open — ral — 2026-10-15 — wave-2 probe-first remainder (B5b): Zeus JAX + NSS n_live_200_mcmc_steps_50, both datasets, 980 runs after the probe under probe-derived @2 timeouts (NSS 600 s…
 
 **Last 5**
 
-- 2026-10-14 — *note* — gaussian_x3@2 frozen (autofit_inference 72d6faaf1717, protocol 11 A2) before any scored run; A4 gate met (PyAutoFit df6d218f1). Dry run 408236 on ral: pin imports, RAL 4-7x faster than the laptop pilot (laptop-derived timeouts are lenient)…
-- 2026-10-14 — *run* — 408367_[0-389] submitted: scored wave 2 separated jax_cpu: 3750 runs, %60, afterany 408346:408347
-- 2026-10-14 — *run* — 408366_[0-379] submitted: scored wave 2 separated numpy: 2250 runs, %60, afterany 408346:408347
-- 2026-10-14 — *run* — 408365_[0-344] submitted: scored wave 2 blend jax_cpu: 3500 runs, %60, afterany 408346:408347
-- 2026-10-14 — *run* — 408348_[0-379] submitted: scored wave 2 (gaussian_x3@2) blend numpy: 2250 runs, 50 seeds x 5 realisations, %60, afterany 408346:408347; submit_wave2_scored_gaussian_x3_blend_numpy
+- 2026-10-15 — *run* — 408367_[0-389] finished — wall 1:57: scored wave 2 separated jax_cpu: 3750 runs, %60, afterany 408346:408347 — 390/390 COMPLETED; 3750 separated jax_cpu rows admitted; judged B5b
+- 2026-10-15 — *run* — 408366_[0-379] finished — wall 1:51: scored wave 2 separated numpy: 2250 runs, %60, afterany 408346:408347 — 380/380 COMPLETED; 2250 separated numpy rows admitted; judged B5b
+- 2026-10-15 — *run* — 408365_[0-344] finished — wall 1:46: scored wave 2 blend jax_cpu: 3500 runs, %60, afterany 408346:408347 — 345/345 COMPLETED; 3500 blend jax_cpu rows admitted; judged B5b
+- 2026-10-15 — *run* — 408348_[0-379] finished — wall 1:53: scored wave 2 (gaussian_x3@2) blend numpy: 2250 runs, 50 seeds x 5 realisations, %60, afterany 408346:408347; submit_wave2_scored_gaussian_x3_blend_numpy — 380/380 COMPLETED; 2250 blend numpy rows admit…
+- 2026-10-15 — *run* — 408347_[0-7] finished — wall 0:01: wave-2 separated reference builds, afterany 408245; %8 — 8/8 COMPLETED; separated reference builds
 
 [full log](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/autofit_inference.md)
 
diff --git a/projects/autofit_inference.md b/projects/autofit_inference.md
index b698ac9..209cf05 100644
--- a/projects/autofit_inference.md
+++ b/projects/autofit_inference.md
@@ -5,22 +5,24 @@ Issue: autofit_inference#8
 
 ## Now
 
-gaussian_x3@2 frozen in autofit_inference 72d6faaf1717 before any scored run (A2+A4 gate met: PyAutoFit df6d218f1). Scored wave 2 submitted 2026-10-14 on RAL ral (11,750 runs + 20-run probe; references first) against a private PyAutoFit pin df6d218f10cd (autofit_inference#9). Next: B5b pulls, builds the JAX blend realisation-1 reference on the laptop, judges under @2.
+Scored wave 2 pulled and judged under gaussian_x3@2 (B5b, 2026-10-15): 11,770 rows at PyAutoFit pin df6d218f10cd all admitted; accounting 11,750 scored (10,580 rows, 1,170 failed) + 20 probe + 250 deferred; all 20 per-realisation references complete (Nautilus-only), JAX blend realisation-1 rebuilt locally. Catalogue gaussian_x3@2 section orders legs within task and dataset (autofit_inference results/accounting, catalogue). Probe-first remainder (980 runs) is 409930 on ral; next: B5b-2 pulls and judges it; wave-2 summary records withheld on size pending autofit_inference#10.
 
 ## Runs
 
-- 408244_[0-49] — running — ral — 2026-10-14 — wave-2 blend references (gaussian_x3@2 freeze 72d6faaf1717): realisations 2-5 x numpy/jax x Nautilus n_live=2000 + DynestyStatic nlive=1000 seeds 0-2, + JAX Nautilus seed 1 realisation 1, + NSS ln 3!; %50; submit_wave2_reference_gaussian_x3_blend; pin PyAutoFit df6d218f10cd
-- 408245_[0-47] — running — ral — 2026-10-14 — wave-2 separated references: realisations 1,3,4,5 x numpy/jax x 6 runs; %48; submit_wave2_reference_gaussian_x3_separated; pin df6d218f10cd
-- 408246_[0-19] — running — ral — 2026-10-14 — wave-2 probe: Zeus JAX + NSS n_live_200_mcmc_steps_50, both datasets, realisation 1, seeds 0-4 (timeouts for probe-first cells); %20; submit_wave2_probe
-- 408346_[0-7] — open — ral — 2026-10-14 — wave-2 blend reference builds (MAP + build_reference), afterany 408244; %8
-- 408347_[0-7] — open — ral — 2026-10-14 — wave-2 separated reference builds, afterany 408245; %8
-- 408348_[0-379] — open — ral — 2026-10-14 — scored wave 2 (gaussian_x3@2) blend numpy: 2250 runs, 50 seeds x 5 realisations, %60, afterany 408346:408347; submit_wave2_scored_gaussian_x3_blend_numpy
-- 408365_[0-344] — open — ral — 2026-10-14 — scored wave 2 blend jax_cpu: 3500 runs, %60, afterany 408346:408347
-- 408366_[0-379] — open — ral — 2026-10-14 — scored wave 2 separated numpy: 2250 runs, %60, afterany 408346:408347
-- 408367_[0-389] — open — ral — 2026-10-14 — scored wave 2 separated jax_cpu: 3750 runs, %60, afterany 408346:408347
+- 409930_[0-19] — open — ral — 2026-10-15 — wave-2 probe-first remainder (B5b): Zeus JAX + NSS n_live_200_mcmc_steps_50, both datasets, 980 runs after the probe under probe-derived @2 timeouts (NSS 600 s, Zeus 1168 s); %20; submit_wave2_remainder; pin df6d218f10cd; pulled in B5b-2
 
 ## Log
 
+- 2026-10-15 — run — 408367_[0-389] finished — wall 1:57: scored wave 2 separated jax_cpu: 3750 runs, %60, afterany 408346:408347 — 390/390 COMPLETED; 3750 separated jax_cpu rows admitted; judged B5b
+- 2026-10-15 — run — 408366_[0-379] finished — wall 1:51: scored wave 2 separated numpy: 2250 runs, %60, afterany 408346:408347 — 380/380 COMPLETED; 2250 separated numpy rows admitted; judged B5b
+- 2026-10-15 — run — 408365_[0-344] finished — wall 1:46: scored wave 2 blend jax_cpu: 3500 runs, %60, afterany 408346:408347 — 345/345 COMPLETED; 3500 blend jax_cpu rows admitted; judged B5b
+- 2026-10-15 — run — 408348_[0-379] finished — wall 1:53: scored wave 2 (gaussian_x3@2) blend numpy: 2250 runs, 50 seeds x 5 realisations, %60, afterany 408346:408347; submit_wave2_scored_gaussian_x3_blend_numpy — 380/380 COMPLETED; 2250 blend numpy rows admitted under gaussian_x3@2; judged B5b
+- 2026-10-15 — run — 408347_[0-7] finished — wall 0:01: wave-2 separated reference builds, afterany 408245; %8 — 8/8 COMPLETED; separated reference builds
+- 2026-10-15 — run — 408346_[0-7] finished — wall 0:01: wave-2 blend reference builds (MAP + build_reference), afterany 408244; %8 — 8/8 COMPLETED; blend reference builds
+- 2026-10-15 — run — 408246_[0-19] finished — wall 0:03: wave-2 probe: Zeus JAX + NSS n_live_200_mcmc_steps_50, both datasets, realisation 1, seeds 0-4 (timeouts for probe-first cells); %20; submit_wave2_probe — 20/20 COMPLETED; probe rows -> @2 timeouts NSS 50-step 600 s (median 26.6 s), Zeus JAX 1168 s (median 116.8 s); pulled B5b
+- 2026-10-15 — run — 408245_[0-47] finished — wall 0:26: wave-2 separated references: realisations 1,3,4,5 x numpy/jax x 6 runs; %48; submit_wave2_reference_gaussian_x3_separated; pin df6d218f10cd — 48/48 COMPLETED; separated references realisations 1,3,4,5 complete (Nautilus-only); pulled B5b
+- 2026-10-15 — run — 408244_[0-49] finished — wall 1:04: wave-2 blend references (gaussian_x3@2 freeze 72d6faaf1717): realisations 2-5 x numpy/jax x Nautilus n_live=2000 + DynestyStatic nlive=1000 seeds 0-2, + JAX Nautilus seed 1 realisation 1, + NSS ln 3!; %50; submit_wave2_reference_gaussian_x3_blend; pin PyAutoFit df6d218f10cd — 50/50 COMPLETED exit 0; blend references realisations 2-5 complete (Nautilus-only: DynestyStatic ln Z disagrees 2.2-7.3 nat), JAX Nautilus seed 1 realisation 1 pulled, NSS ln 3! validated (-1.728); pulled B5b
+- 2026-10-15 — run — 409930_[0-19] submitted: wave-2 probe-first remainder (B5b): Zeus JAX + NSS n_live_200_mcmc_steps_50, both datasets, 980 runs after the probe under probe-derived @2 timeouts (NSS 600 s, Zeus 1168 s); %20; submit_wave2_remainder; pin df6d218f10cd; pulled in B5b-2
 - 2026-10-14 — note — gaussian_x3@2 frozen (autofit_inference 72d6faaf1717, protocol 11 A2) before any scored run; A4 gate met (PyAutoFit df6d218f1). Dry run 408236 on ral: pin imports, RAL 4-7x faster than the laptop pilot (laptop-derived timeouts are lenient); zeus missing from shared venv, carried in the private pin. Survey correction: separated committed realisation is data_seed 2.
 - 2026-10-14 — run — 408367_[0-389] submitted: scored wave 2 separated jax_cpu: 3750 runs, %60, afterany 408346:408347
 - 2026-10-14 — run — 408366_[0-379] submitted: scored wave 2 separated numpy: 2250 runs, %60, afterany 408346:408347
diff --git a/state.json b/state.json
index 64cbd6d..1d02ba9 100644
--- a/state.json
+++ b/state.json
@@ -3,8 +3,8 @@
   "organ": "cortex",
   "repo": "PyAutoCortex",
   "status": "yellow",
-  "headline": "YELLOW \u2014 8 active \u00b7 25 running",
-  "updated": "2026-10-14T16:20:56Z",
+  "headline": "YELLOW \u2014 8 active \u00b7 22 running",
+  "updated": "2026-10-15T15:22:54Z",
   "pages_url": "https://pyautolabs.github.io/PyAutoCortex/",
   "items": [
     {

From 0efc7a6e22c3b67302742f71544d7fba06a6453a Mon Sep 17 00:00:00 2001
From: Jammy2211 <JNightingale2211@gmail.com>
Date: Thu, 15 Oct 2026 16:52:24 +0100
Subject: [PATCH 2/2] cortex: re-render dashboard for the wave-2 ledger (B5b)

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
---
 dashboard.html | 30 +++++++++++-------------------
 dashboard.md   | 28 ++++++++++------------------
 state.json     |  4 ++--
 3 files changed, 23 insertions(+), 39 deletions(-)

diff --git a/dashboard.html b/dashboard.html
index 293dd4e..37df32b 100644
--- a/dashboard.html
+++ b/dashboard.html
@@ -331,11 +331,11 @@
 - Open slope_hierarchy_scale: https://github.com/PyAutoLabs/slope_hierarchy_scale
 - Open ic50_workspace: https://github.com/Jammy2211/ic50_workspace
 - Open autolens_inference: https://github.com/PyAutoLabs/autolens_inference
-- Open autofit_inference: https://github.com/PyAutoLabs/autofit_inference</textarea></details><div class="orchestration-freshness" data-freshness="grey"><details data-freshness-stamp data-refreshed-at="2026-10-15T13:25:33Z"><summary><span data-freshness-label>Last updated 2026-10-15 13:25:33 UTC</span></summary><time datetime="2026-10-15T13:25:33Z">2026-10-15 13:25:33 UTC</time></details><a data-refresh-link href="https://github.com/PyAutoLabs/PyAutoCortex/actions/workflows/dashboard_refresh.yml" title="Open the dashboard refresh controls">↻ Update</a></div></div><p class="orchestration-status" role="status" aria-live="polite"></p></section>
-<nav class="board-nav" aria-label="Board sections"><a class="board-nav-card" href="#summary"><span class="board-nav-count">25</span><span class="board-nav-label">Running</span></a><a class="board-nav-card" href="#summary"><span class="board-nav-count">53</span><span class="board-nav-label">Open</span></a><a class="board-nav-card" href="#projects"><span class="board-nav-count">8</span><span class="board-nav-label">Projects</span></a><a class="board-nav-card" href="#orchestration-cortex"><span class="board-nav-label">Check in</span></a></nav>
+- Open autofit_inference: https://github.com/PyAutoLabs/autofit_inference</textarea></details><div class="orchestration-freshness" data-freshness="grey"><details data-freshness-stamp data-refreshed-at="2026-10-15T15:52:20Z"><summary><span data-freshness-label>Last updated 2026-10-15 15:52:20 UTC</span></summary><time datetime="2026-10-15T15:52:20Z">2026-10-15 15:52:20 UTC</time></details><a data-refresh-link href="https://github.com/PyAutoLabs/PyAutoCortex/actions/workflows/dashboard_refresh.yml" title="Open the dashboard refresh controls">↻ Update</a></div></div><p class="orchestration-status" role="status" aria-live="polite"></p></section>
+<nav class="board-nav" aria-label="Board sections"><a class="board-nav-card" href="#summary"><span class="board-nav-count">22</span><span class="board-nav-label">Running</span></a><a class="board-nav-card" href="#summary"><span class="board-nav-count">48</span><span class="board-nav-label">Open</span></a><a class="board-nav-card" href="#projects"><span class="board-nav-count">8</span><span class="board-nav-label">Projects</span></a><a class="board-nav-card" href="#orchestration-cortex"><span class="board-nav-label">Check in</span></a></nav>
 
 <p class="muted mdsrc"><a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/dashboard.md" class="board-source-link" title="Markdown version" aria-label="Markdown version"><svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.6" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true" focusable="false"><path d="M14 3H6a1 1 0 0 0-1 1v16a1 1 0 0 0 1 1h12a1 1 0 0 0 1-1V8Z"/><path d="M14 3v5h5M8 12h8M8 16h6"/></svg></a></p>
-<details class="board-section"><summary><h2>Summary</h2><span class="section-badge">25 Running · 53 Open</span></summary><div class="board-section-body"><a id="summary"></a>
+<details class="board-section"><summary><h2>Summary</h2><span class="section-badge">22 Running · 48 Open</span></summary><div class="board-section-body"><a id="summary"></a>
 <table class="map">
 <tr><th>Project</th><th>Running</th><th>Open</th><th>Last update</th></tr>
 <tr><td><b>subhalo_validation</b></td><td>0</td><td>5</td><td>2026-09-07</td></tr>
@@ -345,7 +345,7 @@
 <tr><td><b>slope_hierarchy_scale</b></td><td>0</td><td>0</td><td>2026-10-14</td></tr>
 <tr><td><b>ic50_workspace</b></td><td>0</td><td>0</td><td>2026-10-14</td></tr>
 <tr><td><b>autolens_inference</b></td><td>6</td><td>0</td><td>2026-09-24</td></tr>
-<tr><td><b>autofit_inference</b></td><td>3</td><td>6</td><td>2026-10-14</td></tr>
+<tr><td><b>autofit_inference</b></td><td>0</td><td>1</td><td>2026-10-15</td></tr>
 </table>
 </div></details><details class="board-section"><summary><h2>Projects</h2><span class="section-badge">8</span></summary><div class="board-section-body"><a id="projects"></a>
 <section class="project">
@@ -550,26 +550,18 @@ <h3>autolens_inference — Do the PyAutoLens inference backends agree on the HST
 <h3>autofit_inference — PyAutoFit search benchmark on gaussian_x3: which searches find the right answer fastest</h3>
 <p class="muted">active · ral · <a href="https://github.com/PyAutoLabs/autofit_inference/issues/8">autofit_inference#8</a> · <a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/autofit_inference.md">projects/autofit_inference.md</a> · local <span class="pathchip">/home/jammy/Code/PyAutoLabs/fit/autofit_inference</span> · RAL <span class="pathchip">/mnt/ral/jnightin/autofit_inference</span></p>
 <p><b>Now</b></p>
-<p>gaussian_x3@2 frozen in autofit_inference 72d6faaf1717 before any scored run (A2+A4 gate met: PyAutoFit df6d218f1). Scored wave 2 submitted 2026-10-14 on RAL ral (11,750 runs + 20-run probe; references first) against a private PyAutoFit pin df6d218f10cd (autofit_inference#9). Next: B5b pulls, builds the JAX blend realisation-1 reference on the laptop, judges under @2.</p>
+<p>Scored wave 2 pulled and judged under gaussian_x3@2 (B5b, 2026-10-15): 11,770 rows at PyAutoFit pin df6d218f10cd all admitted; accounting 11,750 scored (10,580 rows, 1,170 failed) + 20 probe + 250 deferred; all 20 per-realisation references complete (Nautilus-only), JAX blend realisation-1 rebuilt locally. Catalogue gaussian_x3@2 section orders legs within task and dataset (autofit_inference results/accounting, catalogue). Probe-first remainder (980 runs) is 409930 on ral; next: B5b-2 pulls and judges it; wave-2 summary records withheld on size pending autofit_inference#10.</p>
 <p><b>Runs</b></p>
 <ul>
-<li>408244_[0-49] — running — ral — 2026-10-14 — wave-2 blend references (gaussian_x3@2 freeze 72d6faaf1717): realisations 2-5 x numpy/jax x Nautilus n_live=2000 + DynestyStatic nlive=1000 seeds 0-2, + JAX Na…</li>
-<li>408245_[0-47] — running — ral — 2026-10-14 — wave-2 separated references: realisations 1,3,4,5 x numpy/jax x 6 runs; %48; submit_wave2_reference_gaussian_x3_separated; pin df6d218f10cd</li>
-<li>408246_[0-19] — running — ral — 2026-10-14 — wave-2 probe: Zeus JAX + NSS n_live_200_mcmc_steps_50, both datasets, realisation 1, seeds 0-4 (timeouts for probe-first cells); %20; submit_wave2_probe</li>
-<li>408346_[0-7] — open — ral — 2026-10-14 — wave-2 blend reference builds (MAP + build_reference), afterany 408244; %8</li>
-<li>408347_[0-7] — open — ral — 2026-10-14 — wave-2 separated reference builds, afterany 408245; %8</li>
-<li>408348_[0-379] — open — ral — 2026-10-14 — scored wave 2 (gaussian_x3@2) blend numpy: 2250 runs, 50 seeds x 5 realisations, %60, afterany 408346:408347; submit_wave2_scored_gaussian_x3_blend_numpy</li>
-<li>408365_[0-344] — open — ral — 2026-10-14 — scored wave 2 blend jax_cpu: 3500 runs, %60, afterany 408346:408347</li>
-<li>408366_[0-379] — open — ral — 2026-10-14 — scored wave 2 separated numpy: 2250 runs, %60, afterany 408346:408347</li>
-<li>408367_[0-389] — open — ral — 2026-10-14 — scored wave 2 separated jax_cpu: 3750 runs, %60, afterany 408346:408347</li>
+<li>409930_[0-19] — open — ral — 2026-10-15 — wave-2 probe-first remainder (B5b): Zeus JAX + NSS n_live_200_mcmc_steps_50, both datasets, 980 runs after the probe under probe-derived @2 timeouts (NSS 600 s…</li>
 </ul>
 <p><b>Last 5</b></p>
 <ul>
-<li>2026-10-14 — <i>note</i> — gaussian_x3@2 frozen (autofit_inference 72d6faaf1717, protocol 11 A2) before any scored run; A4 gate met (PyAutoFit df6d218f1). Dry run 408236 on ral: pin imports, RAL 4-7x faster than the laptop pilot (laptop-derived timeouts are lenient)…</li>
-<li>2026-10-14 — <i>run</i> — 408367_[0-389] submitted: scored wave 2 separated jax_cpu: 3750 runs, %60, afterany 408346:408347</li>
-<li>2026-10-14 — <i>run</i> — 408366_[0-379] submitted: scored wave 2 separated numpy: 2250 runs, %60, afterany 408346:408347</li>
-<li>2026-10-14 — <i>run</i> — 408365_[0-344] submitted: scored wave 2 blend jax_cpu: 3500 runs, %60, afterany 408346:408347</li>
-<li>2026-10-14 — <i>run</i> — 408348_[0-379] submitted: scored wave 2 (gaussian_x3@2) blend numpy: 2250 runs, 50 seeds x 5 realisations, %60, afterany 408346:408347; submit_wave2_scored_gaussian_x3_blend_numpy</li>
+<li>2026-10-15 — <i>run</i> — 408367_[0-389] finished — wall 1:57: scored wave 2 separated jax_cpu: 3750 runs, %60, afterany 408346:408347 — 390/390 COMPLETED; 3750 separated jax_cpu rows admitted; judged B5b</li>
+<li>2026-10-15 — <i>run</i> — 408366_[0-379] finished — wall 1:51: scored wave 2 separated numpy: 2250 runs, %60, afterany 408346:408347 — 380/380 COMPLETED; 2250 separated numpy rows admitted; judged B5b</li>
+<li>2026-10-15 — <i>run</i> — 408365_[0-344] finished — wall 1:46: scored wave 2 blend jax_cpu: 3500 runs, %60, afterany 408346:408347 — 345/345 COMPLETED; 3500 blend jax_cpu rows admitted; judged B5b</li>
+<li>2026-10-15 — <i>run</i> — 408348_[0-379] finished — wall 1:53: scored wave 2 (gaussian_x3@2) blend numpy: 2250 runs, 50 seeds x 5 realisations, %60, afterany 408346:408347; submit_wave2_scored_gaussian_x3_blend_numpy — 380/380 COMPLETED; 2250 blend numpy rows admit…</li>
+<li>2026-10-15 — <i>run</i> — 408347_[0-7] finished — wall 0:01: wave-2 separated reference builds, afterany 408245; %8 — 8/8 COMPLETED; separated reference builds</li>
 </ul>
 <p class="muted"><a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/autofit_inference.md">full log</a></p>
 <div class="task"><button class="copy" data-cmd="Use the cortex skill. — resume autofit_inference: read PyAutoCortex projects/autofit_inference.md (Now, Runs, Log) and then /home/jammy/Code/PyAutoLabs/fit/autofit_inference/wiki/project/state.md and the assistant autofit_assistant's AGENTS.md; tell me where I left off and what I said I would do next. Submit nothing and log nothing until I say." aria-label="Copy the AI command">📋</button><p>resume autofit_inference</p></div>
diff --git a/dashboard.md b/dashboard.md
index 65858df..a4f7957 100644
--- a/dashboard.md
+++ b/dashboard.md
@@ -10,8 +10,8 @@ One ledger per science project: what is on the cluster right now, what the human
 
 | Where | Count |
 |-------|------:|
-| [Running](#projects) | 25 |
-| [Open](#projects) | 53 |
+| [Running](#projects) | 22 |
+| [Open](#projects) | 48 |
 | [Projects](#projects) | 8 |
 
 <details><summary>📋 check in since last time</summary>
@@ -49,7 +49,7 @@ Last check-in: 2026-09-30T09:51Z.
 | slope_hierarchy_scale | 0 | 0 | 2026-10-14 |
 | ic50_workspace | 0 | 0 | 2026-10-14 |
 | autolens_inference | 6 | 0 | 2026-09-24 |
-| autofit_inference | 3 | 6 | 2026-10-14 |
+| autofit_inference | 0 | 1 | 2026-10-15 |
 
 ## Projects
 
@@ -336,27 +336,19 @@ active · ral · [autofit_inference#8](https://github.com/PyAutoLabs/autofit_inf
 
 **Now**
 
-gaussian_x3@2 frozen in autofit_inference 72d6faaf1717 before any scored run (A2+A4 gate met: PyAutoFit df6d218f1). Scored wave 2 submitted 2026-10-14 on RAL ral (11,750 runs + 20-run probe; references first) against a private PyAutoFit pin df6d218f10cd (autofit_inference#9). Next: B5b pulls, builds the JAX blend realisation-1 reference on the laptop, judges under @2.
+Scored wave 2 pulled and judged under gaussian_x3@2 (B5b, 2026-10-15): 11,770 rows at PyAutoFit pin df6d218f10cd all admitted; accounting 11,750 scored (10,580 rows, 1,170 failed) + 20 probe + 250 deferred; all 20 per-realisation references complete (Nautilus-only), JAX blend realisation-1 rebuilt locally. Catalogue gaussian_x3@2 section orders legs within task and dataset (autofit_inference results/accounting, catalogue). Probe-first remainder (980 runs) is 409930 on ral; next: B5b-2 pulls and judges it; wave-2 summary records withheld on size pending autofit_inference#10.
 
 **Runs**
 
-- 408244_[0-49] — running — ral — 2026-10-14 — wave-2 blend references (gaussian_x3@2 freeze 72d6faaf1717): realisations 2-5 x numpy/jax x Nautilus n_live=2000 + DynestyStatic nlive=1000 seeds 0-2, + JAX Na…
-- 408245_[0-47] — running — ral — 2026-10-14 — wave-2 separated references: realisations 1,3,4,5 x numpy/jax x 6 runs; %48; submit_wave2_reference_gaussian_x3_separated; pin df6d218f10cd
-- 408246_[0-19] — running — ral — 2026-10-14 — wave-2 probe: Zeus JAX + NSS n_live_200_mcmc_steps_50, both datasets, realisation 1, seeds 0-4 (timeouts for probe-first cells); %20; submit_wave2_probe
-- 408346_[0-7] — open — ral — 2026-10-14 — wave-2 blend reference builds (MAP + build_reference), afterany 408244; %8
-- 408347_[0-7] — open — ral — 2026-10-14 — wave-2 separated reference builds, afterany 408245; %8
-- 408348_[0-379] — open — ral — 2026-10-14 — scored wave 2 (gaussian_x3@2) blend numpy: 2250 runs, 50 seeds x 5 realisations, %60, afterany 408346:408347; submit_wave2_scored_gaussian_x3_blend_numpy
-- 408365_[0-344] — open — ral — 2026-10-14 — scored wave 2 blend jax_cpu: 3500 runs, %60, afterany 408346:408347
-- 408366_[0-379] — open — ral — 2026-10-14 — scored wave 2 separated numpy: 2250 runs, %60, afterany 408346:408347
-- 408367_[0-389] — open — ral — 2026-10-14 — scored wave 2 separated jax_cpu: 3750 runs, %60, afterany 408346:408347
+- 409930_[0-19] — open — ral — 2026-10-15 — wave-2 probe-first remainder (B5b): Zeus JAX + NSS n_live_200_mcmc_steps_50, both datasets, 980 runs after the probe under probe-derived @2 timeouts (NSS 600 s…
 
 **Last 5**
 
-- 2026-10-14 — *note* — gaussian_x3@2 frozen (autofit_inference 72d6faaf1717, protocol 11 A2) before any scored run; A4 gate met (PyAutoFit df6d218f1). Dry run 408236 on ral: pin imports, RAL 4-7x faster than the laptop pilot (laptop-derived timeouts are lenient)…
-- 2026-10-14 — *run* — 408367_[0-389] submitted: scored wave 2 separated jax_cpu: 3750 runs, %60, afterany 408346:408347
-- 2026-10-14 — *run* — 408366_[0-379] submitted: scored wave 2 separated numpy: 2250 runs, %60, afterany 408346:408347
-- 2026-10-14 — *run* — 408365_[0-344] submitted: scored wave 2 blend jax_cpu: 3500 runs, %60, afterany 408346:408347
-- 2026-10-14 — *run* — 408348_[0-379] submitted: scored wave 2 (gaussian_x3@2) blend numpy: 2250 runs, 50 seeds x 5 realisations, %60, afterany 408346:408347; submit_wave2_scored_gaussian_x3_blend_numpy
+- 2026-10-15 — *run* — 408367_[0-389] finished — wall 1:57: scored wave 2 separated jax_cpu: 3750 runs, %60, afterany 408346:408347 — 390/390 COMPLETED; 3750 separated jax_cpu rows admitted; judged B5b
+- 2026-10-15 — *run* — 408366_[0-379] finished — wall 1:51: scored wave 2 separated numpy: 2250 runs, %60, afterany 408346:408347 — 380/380 COMPLETED; 2250 separated numpy rows admitted; judged B5b
+- 2026-10-15 — *run* — 408365_[0-344] finished — wall 1:46: scored wave 2 blend jax_cpu: 3500 runs, %60, afterany 408346:408347 — 345/345 COMPLETED; 3500 blend jax_cpu rows admitted; judged B5b
+- 2026-10-15 — *run* — 408348_[0-379] finished — wall 1:53: scored wave 2 (gaussian_x3@2) blend numpy: 2250 runs, 50 seeds x 5 realisations, %60, afterany 408346:408347; submit_wave2_scored_gaussian_x3_blend_numpy — 380/380 COMPLETED; 2250 blend numpy rows admit…
+- 2026-10-15 — *run* — 408347_[0-7] finished — wall 0:01: wave-2 separated reference builds, afterany 408245; %8 — 8/8 COMPLETED; separated reference builds
 
 [full log](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/autofit_inference.md)
 
diff --git a/state.json b/state.json
index 02afcd9..10bd457 100644
--- a/state.json
+++ b/state.json
@@ -3,8 +3,8 @@
   "organ": "cortex",
   "repo": "PyAutoCortex",
   "status": "yellow",
-  "headline": "YELLOW \u2014 8 active \u00b7 25 running",
-  "updated": "2026-10-15T13:25:33Z",
+  "headline": "YELLOW \u2014 8 active \u00b7 22 running",
+  "updated": "2026-10-15T15:52:20Z",
   "pages_url": "https://pyautolabs.github.io/PyAutoCortex/",
   "items": [
     {