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20 changes: 10 additions & 10 deletions dashboard.html
Original file line number Diff line number Diff line change
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<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 2026-10-15 — regenerate, do not hand-edit -->
<!-- generated by `pyauto-brain cortex dashboard --apply` on 2026-10-16 — 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;
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- Open autolens_inference: https://github.com/PyAutoLabs/autolens_inference
- Open autofit_inference: https://github.com/PyAutoLabs/autofit_inference
- Open euclid_detailed: https://github.com/PyAutoLabs/euclid_detailed
- Open cowls: https://github.com/PyAutoLabs/cowls</textarea></details><div class="orchestration-freshness" data-freshness="grey"><details data-freshness-stamp data-refreshed-at="2026-10-15T20:54:57Z"><summary><span data-freshness-label>Last updated 2026-10-15 20:54:57 UTC</span></summary><time datetime="2026-10-15T20:54:57Z">2026-10-15 20:54:57 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>
- Open cowls: https://github.com/PyAutoLabs/cowls</textarea></details><div class="orchestration-freshness" data-freshness="grey"><details data-freshness-stamp data-refreshed-at="2026-10-16T10:04:26Z"><summary><span data-freshness-label>Last updated 2026-10-16 10:04:26 UTC</span></summary><time datetime="2026-10-16T10:04:26Z">2026-10-16 10:04:26 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">47</span><span class="board-nav-label">Open</span></a><a class="board-nav-card" href="#projects"><span class="board-nav-count">11</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>
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<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>0</td><td>0</td><td>2026-10-15</td></tr>
<tr><td><b>autofit_inference</b></td><td>0</td><td>0</td><td>2026-10-16</td></tr>
<tr><td><b>euclid_detailed</b></td><td>0</td><td>0</td><td>2026-10-15</td></tr>
<tr><td><b>cowls</b></td><td>0</td><td>0</td><td>2026-10-15</td></tr>
</table>
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</div>
</details>
<details class="project" id="project-autofit_inference">
<summary><h3>autofit_inference</h3><span class="purpose">PyAutoFit search benchmark on gaussian_x3: which searches find the right answer fastest</span><span class="meta">no runs recorded · updated 2026-10-15</span></summary>
<summary><h3>autofit_inference</h3><span class="purpose">PyAutoFit search benchmark on gaussian_x3: which searches find the right answer fastest</span><span class="meta">no runs recorded · updated 2026-10-16</span></summary>
<div class="project-body">
<dl class="where">
<dt>Registered:</dt><dd>2026-10-08</dd>
<dt>Local:</dt><dd>/home/jammy/Code/PyAutoLabs/fit/autofit_inference</dd>
<dt>RAL:</dt><dd>/mnt/ral/jnightin/inference/autofit_inference</dd>
</dl><div class="position"><div class="position-text">
<h4>Current position</h4>
<p>Wave 2 closed and judged under gaussian_x3@2 (B5b-2, 2026-10-15): all 12,750 pulled rows admitted at PyAutoFit pin df6d218f10cd; of the 13,000 expected runs, 11,580 rows + 1,170 failed + 0 missing + 250 deferred. The 409930 probe-first legs close: NSS 50-step leads both evidence rankings (blend 158/250, separated 210/250); Zeus JAX is 0/250 on the blend and 190/250 on the separated control (first among separated posterior legs). The catalogue ranks only legs with success rate &gt;= 50 % over &gt;= 20 attempts and lists the rest as unreliable (post-hoc presentation convention, protocol §8 note; autofit_inference#12 ruling 2). Summary records published as inference-summary@3 (101 record shards). Next: after the B5b-2 PRs merge, capture the Insight fit snapshot from main under @3 and run pyauto-insight check online; then B5c (a second model family).</p></div>
<p>B5c (2026-10-15, autofit_inference#14): a second model family, correlated_nd (correlated Gaussians D = 20/50/100, condition number 10^3, and a D = 20 hybrid Rosenbrock banana, exact posteriors and ln Z), pre-registered as correlated_nd@1 (first committed 9ec37795f404; amendment A1 before any row) with seeded datasets and eight exact references that pass the section 6 agreement test. Its 930-run pilot RAL 410866 finished 2026-10-16 (926/930 completed, 4 OUT_OF_MEMORY at 8 G on corr_gaussian_d50, carried to B5c-2; 409957 failed at import on the disturbed shared clone and was cancelled) on --partition=ral from the private copy inference/autofit_inference_b5c at the pin df6d218f10cd; it ranks nothing and is catalogued apart from gaussian_x3 (nothing ranked across families). gaussian_x3 wave 2 stays closed and judged under gaussian_x3@2. Next: B5c-2 pulls the pilot (results/ only) from the private copy, settles the 4 OOM cells (more memory or excluded), judges it under @1, freezes correlated_nd@2 and submits the scored wave.</p></div>
<button class="copy resume" aria-label="Copy resume prompt for autofit_inference" title="Copy resume prompt for autofit_inference" 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.">📋</button>
</div>
<h4>Runs (0)</h4>
<p class="muted">nothing on the cluster</p>
<details class="sub"><summary>Recent log — 5 of 23 entries</summary>
<details class="sub"><summary>Recent log — 5 of 27 entries</summary>
<ul class="log">
<li>2026-10-16 — <i>run</i> — <details class="full"><summary><span class="clip">410866_[0-929] finished — wall 4:16: correlated_nd@1 pilot (B5c), resubmission of 409957 from the PRIVATE copy /mnt/ral/jnightin/inference/autofit_inference_b5c (delivered files sha256-verified from 245a3ef, own copy of the pin): 930 runs,…</span><span class="less">show less</span></summary><p>410866_[0-929] finished — wall 4:16: correlated_nd@1 pilot (B5c), resubmission of 409957 from the PRIVATE copy /mnt/ral/jnightin/inference/autofit_inference_b5c (delivered files sha256-verified from 245a3ef, own copy of the pin): 930 runs, 10 seeds x realisation 1 x 93 planned cells, one run per task, 4 h process cap, %100; pin df6d218f10cd; pull results/ from the private copy in B5c-2 — 926/930 COMPLETED, 4 OUT_OF_MEMORY at 8 G, all corr_gaussian_d50: task 263 nautilus n_live_100 numpy seed 3, 273 nautilus n_live_100 jax_cpu seed 3, 304 nautilus n_live_400 numpy seed 4, 383 blackjax_nuts_warm warmup_200_samples_500 jax_cpu seed 3; not rerun in stage 1 (human decision), B5c-2 raises their memory or excludes them; results unpulled in the private copy, pulled and judged in B5c-2</p></details></li>
<li>2026-10-15 — <i>run</i> — <details class="full"><summary><span class="clip">410866_[0-929] submitted: correlated_nd@1 pilot (B5c), resubmission of 409957 from the PRIVATE copy /mnt/ral/jnightin/inference/autofit_inference_b5c (delivered files sha256-verified from 245a3ef, own copy of the pin): 930 runs, 10 seeds x…</span><span class="less">show less</span></summary><p>410866_[0-929] submitted: correlated_nd@1 pilot (B5c), resubmission of 409957 from the PRIVATE copy /mnt/ral/jnightin/inference/autofit_inference_b5c (delivered files sha256-verified from 245a3ef, own copy of the pin): 930 runs, 10 seeds x realisation 1 x 93 planned cells, one run per task, 4 h process cap, %100; pin df6d218f10cd; pull results/ from the private copy in B5c-2</p></details></li>
<li>2026-10-15 — <i>run</i> — <details class="full"><summary><span class="clip">409957_[0-929] failed — wall 0:06: correlated_nd@1 pilot (B5c, second model family; protocol first committed 9ec37795f404, A1 before any row): 930 runs, 10 seeds x realisation 1 x 93 planned cells over corr_gaussian_d20/d50/d100 + rosenbro…</span><span class="less">show less</span></summary><p>409957_[0-929] failed — wall 0:06: correlated_nd@1 pilot (B5c, second model family; protocol first committed 9ec37795f404, A1 before any row): 930 runs, 10 seeds x realisation 1 x 93 planned cells over corr_gaussian_d20/d50/d100 + rosenbrock_d20, one run per task, 4 h process cap, %100; submit_correlated_nd_pilot; pin df6d218f10cd; pulled in B5c-2 — every task failed at import (ModuleNotFoundError _autofit_inference_cli): the shared RAL clone had been switched to an old main by another session (stash pre-main-switch 19:24 UTC) and lost the CLI and config/ as the array started; 800 tasks exited, the rest scancelled; no row written; resubmitted from the private copy inference/autofit_inference_b5c as 410866</p></details></li>
<li>2026-10-15 — <i>run</i> — <details class="full"><summary><span class="clip">409957_[0-929] submitted: correlated_nd@1 pilot (B5c, second model family; protocol first committed 9ec37795f404, A1 before any row): 930 runs, 10 seeds x realisation 1 x 93 planned cells over corr_gaussian_d20/d50/d100 + rosenbrock_d20, o…</span><span class="less">show less</span></summary><p>409957_[0-929] submitted: correlated_nd@1 pilot (B5c, second model family; protocol first committed 9ec37795f404, A1 before any row): 930 runs, 10 seeds x realisation 1 x 93 planned cells over corr_gaussian_d20/d50/d100 + rosenbrock_d20, one run per task, 4 h process cap, %100; submit_correlated_nd_pilot; pin df6d218f10cd; pulled in B5c-2</p></details></li>
<li>2026-10-15 — <i>run</i> — <details class="full"><summary><span class="clip">409930_[0-19] finished — wall 1:30: 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;…</span><span class="less">show less</span></summary><p>409930_[0-19] finished — wall 1:30: 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 — 20/20 COMPLETED (16:08-17:38 UTC); 980 remainder rows pulled by per-directory tar (20 probe rows byte-identical); all admitted under gaussian_x3@2, 0 missing; judged B5b-2</p></details></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> — <details class="full"><summary><span class="clip">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…</span><span class="less">show less</span></summary><p>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</p></details></li>
</ul>
<p class="muted"><a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/autofit_inference.md">full log</a></p>
<p class="muted">active · ral · <a href="https://github.com/PyAutoLabs/autofit_inference/issues/8">autofit_inference#8</a></p>
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