projects.yaml: analytic_gaussian, ep_toy_gaussian → active/

dashboard.html

@@ -331,7 +331,7 @@
 - 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>
+- 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="2026-10-15T15:48:28Z"><summary><span data-freshness-label>Last updated 2026-10-15 15:48:28 UTC</span></summary><time datetime="2026-10-15T15:48:28Z">2026-10-15 15:48:28 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>
 
 <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>
@@ -451,7 +451,7 @@ <h3>euclid_dr1 — Does the sep1 DR1 delivery reproduce the ten prelim lenses by
 </section>
 <section class="project">
 <h3>analytic_gaussian — Graphical and EP against a closed-form Gaussian posterior, at ensemble scale</h3>
-<p class="muted">active · ral · <a href="https://github.com/PyAutoLabs/PyAutoCortex/issues/34">PyAutoCortex#34</a> · <a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/analytic_gaussian.md">projects/analytic_gaussian.md</a> · local <span class="pathchip">/mnt/c/Users/Jammy/Science/inference/analytic_gaussian</span> · RAL <span class="pathchip">/mnt/ral/jnightin/analytic_gaussian</span></p>
+<p class="muted">active · ral · <a href="https://github.com/PyAutoLabs/PyAutoCortex/issues/34">PyAutoCortex#34</a> · <a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/analytic_gaussian.md">projects/analytic_gaussian.md</a> · local <span class="pathchip">/mnt/c/Users/Jammy/Science/active/analytic_gaussian</span> · RAL <span class="pathchip">/mnt/ral/jnightin/active/analytic_gaussian</span></p>
 <p><b>Now</b></p>
 <p>Wave 1 (342413, 200 seeds at N=5) is accepted as the baseline: autofit EP is exact on the Gaussian leg, leg B sigma misses as pre-registered (78/200), collapse rate 0/200. On criterion 2, astra and an independent Opus review both favour an under-calibrated mu threshold (calibrated on five unrepresentative seeds) and found no defect in the minimal-EP control; both flag the per-site sigma&gt;0 clip (analytic_ep_minimal.py:333) as the one audit target, and astra will not clear the control without an independent reconstruction of the EP fixed point. Next: run the planned diagnostic (archive/tasks/analytic_gaussian/minimal_ep_legb_mu_threshold.md) on a passing, an edge and the worst mu seed; the N=25 rung stays written but unsubmitted until it lands.</p>
 <p><b>Runs</b></p>
@@ -465,11 +465,11 @@ <h3>analytic_gaussian — Graphical and EP against a closed-form Gaussian poster
 <li>2026-09-10 — <i>note</i> — question: Is criterion 2's mu threshold or the minimal-EP control wrong — planned, never run [archive/tasks/analytic_gaussian/minimal_ep_legb_mu_threshold.md]</li>
 </ul>
 <p class="muted"><a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/analytic_gaussian.md">full log</a></p>
-<div class="task"><button class="copy" data-cmd="Use the cortex skill. — resume analytic_gaussian: read PyAutoCortex projects/analytic_gaussian.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/inference/analytic_gaussian/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 analytic_gaussian</p></div>
+<div class="task"><button class="copy" data-cmd="Use the cortex skill. — resume analytic_gaussian: read PyAutoCortex projects/analytic_gaussian.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/active/analytic_gaussian/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 analytic_gaussian</p></div>
 </section>
 <section class="project">
 <h3>ep_toy_gaussian — NUTS versus three EP fits on the #1405 collapse toy at N=50</h3>
-<p class="muted">active · ral · <a href="https://github.com/PyAutoLabs/ep_toy_gaussian/issues/1">ep_toy_gaussian#1</a> · <a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/ep_toy_gaussian.md">projects/ep_toy_gaussian.md</a> · local <span class="pathchip">/mnt/c/Users/Jammy/Science/inference/ep_toy_gaussian</span> · RAL <span class="pathchip">/mnt/ral/jnightin/ep_toy_gaussian</span></p>
+<p class="muted">active · ral · <a href="https://github.com/PyAutoLabs/ep_toy_gaussian/issues/1">ep_toy_gaussian#1</a> · <a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/ep_toy_gaussian.md">projects/ep_toy_gaussian.md</a> · local <span class="pathchip">/mnt/c/Users/Jammy/Science/active/ep_toy_gaussian</span> · RAL <span class="pathchip">/mnt/ral/jnightin/active/ep_toy_gaussian</span></p>
 <p><b>Now</b></p>
 <p>Wave 1 (n50_seed42: 342639 + 342640_[0-2]) failed on infrastructure — EP x3 on EMFILE (fixed by PyAutoFit#1632/#1634, both in the RAL mirror at 404b3e5f7), NUTS on OOM at the 8 GB cap while XLA compiled the 50-factor window-adaptation scan, which grows with N (≥5.4 GB at N=20 locally). Wave 2 is prepared but not submitted: sample n50_seed42_w2 (free locally and on RAL; still needs its toy.SAMPLES entry), submit_nuts raised to 64 GB, submit_ep unchanged at 8 GB (peak ~590 MB). The collapse question at N=50 is unanswered; only n5_smoke speaks (EP RECOVER 3/3, NUTS 49.89/11.14). Next: human go, add the sample entry, push and submit NUTS then EP with SAMPLE=n50_seed42_w2 exported.</p>
 <p><b>Runs</b></p>
@@ -483,7 +483,7 @@ <h3>ep_toy_gaussian — NUTS versus three EP fits on the #1405 collapse toy at N
 <li>2026-09-24 — <i>note</i> — per-search overhead profile on this toy (2026-09-24, laptop, N=5, max_steps=3): 2.45 s per Dynesty factor search, ~1.47 s dynesty run_nested + ~0.98 s autofit wrapper (plots, a redundant second run_nested pass, samples writes); inside run_…</li>
 </ul>
 <p class="muted"><a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/ep_toy_gaussian.md">full log</a></p>
-<div class="task"><button class="copy" data-cmd="Use the cortex skill. — resume ep_toy_gaussian: read PyAutoCortex projects/ep_toy_gaussian.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/inference/ep_toy_gaussian/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 ep_toy_gaussian</p></div>
+<div class="task"><button class="copy" data-cmd="Use the cortex skill. — resume ep_toy_gaussian: read PyAutoCortex projects/ep_toy_gaussian.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/active/ep_toy_gaussian/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 ep_toy_gaussian</p></div>
 </section>
 <section class="project">
 <h3>slope_hierarchy_scale — Hierarchical slope recovery with graphical and EP at N=25 to 50</h3>

dashboard.md

@@ -177,7 +177,7 @@ Use the cortex skill. — resume euclid_dr1: read PyAutoCortex projects/euclid_d
 
 ### analytic_gaussian — Graphical and EP against a closed-form Gaussian posterior, at ensemble scale
 
-active · ral · [PyAutoCortex#34](https://github.com/PyAutoLabs/PyAutoCortex/issues/34) · [projects/analytic_gaussian.md](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/analytic_gaussian.md) · local `/mnt/c/Users/Jammy/Science/inference/analytic_gaussian` · RAL `/mnt/ral/jnightin/analytic_gaussian`
+active · ral · [PyAutoCortex#34](https://github.com/PyAutoLabs/PyAutoCortex/issues/34) · [projects/analytic_gaussian.md](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/analytic_gaussian.md) · local `/mnt/c/Users/Jammy/Science/active/analytic_gaussian` · RAL `/mnt/ral/jnightin/active/analytic_gaussian`
 
 **Now**
 
@@ -200,14 +200,14 @@ Wave 1 (342413, 200 seeds at N=5) is accepted as the baseline: autofit EP is exa
 <details><summary>📋 resume analytic_gaussian</summary>
 
 ```
-Use the cortex skill. — resume analytic_gaussian: read PyAutoCortex projects/analytic_gaussian.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/inference/analytic_gaussian/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.
+Use the cortex skill. — resume analytic_gaussian: read PyAutoCortex projects/analytic_gaussian.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/active/analytic_gaussian/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.
 ```
 
 </details>
 
 ### ep_toy_gaussian — NUTS versus three EP fits on the #1405 collapse toy at N=50
 
-active · ral · [ep_toy_gaussian#1](https://github.com/PyAutoLabs/ep_toy_gaussian/issues/1) · [projects/ep_toy_gaussian.md](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/ep_toy_gaussian.md) · local `/mnt/c/Users/Jammy/Science/inference/ep_toy_gaussian` · RAL `/mnt/ral/jnightin/ep_toy_gaussian`
+active · ral · [ep_toy_gaussian#1](https://github.com/PyAutoLabs/ep_toy_gaussian/issues/1) · [projects/ep_toy_gaussian.md](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/ep_toy_gaussian.md) · local `/mnt/c/Users/Jammy/Science/active/ep_toy_gaussian` · RAL `/mnt/ral/jnightin/active/ep_toy_gaussian`
 
 **Now**
 
@@ -230,7 +230,7 @@ Wave 1 (n50_seed42: 342639 + 342640_[0-2]) failed on infrastructure — EP x3 on
 <details><summary>📋 resume ep_toy_gaussian</summary>
 
 ```
-Use the cortex skill. — resume ep_toy_gaussian: read PyAutoCortex projects/ep_toy_gaussian.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/inference/ep_toy_gaussian/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.
+Use the cortex skill. — resume ep_toy_gaussian: read PyAutoCortex projects/ep_toy_gaussian.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/active/ep_toy_gaussian/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.
 ```
 
 </details>

projects.yaml

@@ -117,8 +117,8 @@ euclid_dr1:
 
 analytic_gaussian:
   remote: none
-  local_path: /mnt/c/Users/Jammy/Science/inference/analytic_gaussian
-  ral_root: /mnt/ral/jnightin/analytic_gaussian
+  local_path: /mnt/c/Users/Jammy/Science/active/analytic_gaussian
+  ral_root: /mnt/ral/jnightin/active/analytic_gaussian
   mirror: none
   sync_cli: hpc/sync
   sync_verbs: [push, pull, logs, sync, status, submit, push-submit, jobs, sacct, cancel, tail, du, check]
@@ -131,8 +131,8 @@ analytic_gaussian:
 
 ep_toy_gaussian:
   remote: PyAutoLabs/ep_toy_gaussian
-  local_path: /mnt/c/Users/Jammy/Science/inference/ep_toy_gaussian
-  ral_root: /mnt/ral/jnightin/ep_toy_gaussian
+  local_path: /mnt/c/Users/Jammy/Science/active/ep_toy_gaussian
+  ral_root: /mnt/ral/jnightin/active/ep_toy_gaussian
   mirror: none
   sync_cli: hpc/sync
   sync_verbs: [push, pull, logs, sync, status, submit, push-submit, jobs, sacct, cancel, tail, du, check]

state.json

@@ -4,7 +4,7 @@
   "repo": "PyAutoCortex",
   "status": "yellow",
   "headline": "YELLOW \u2014 8 active \u00b7 25 running",
-  "updated": "2026-10-15T13:25:33Z",
+  "updated": "2026-10-15T15:48:29Z",
   "pages_url": "https://pyautolabs.github.io/PyAutoCortex/",
   "items": [
     {