From 4c2574d01ea02277f8f6284070d9fc0eca2983c0 Mon Sep 17 00:00:00 2001
From: Jammy2211 <JNightingale2211@gmail.com>
Date: Thu, 15 Oct 2026 13:59:10 +0100
Subject: [PATCH 1/2] projects.yaml: point science paths at real folders, not
 compat symlinks

The Science/ restructure (active/, inference/, archive/, complete/) left
top-level compatibility symlinks that clutter PyCharm. Repoint every
local_path/mirror at the real folder so the symlinks can be removed.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 projects.yaml | 30 +++++++++++++++---------------
 1 file changed, 15 insertions(+), 15 deletions(-)

diff --git a/projects.yaml b/projects.yaml
index 2aa5f06..9b88bf7 100644
--- a/projects.yaml
+++ b/projects.yaml
@@ -49,7 +49,7 @@ inference_programme:
   remote: PyAutoLabs/autolens_profiling
   local_path: /home/jammy/Code/PyAutoLabs/lens/autolens_profiling
   ral_root: /mnt/ral/jnightin/autolens_profiling
-  mirror: /mnt/c/Users/Jammy/Science/z_vault/inference_programme
+  mirror: /mnt/c/Users/Jammy/Science/archive/inference_programme
   sync_cli: hpc/sync
   sync_verbs: [pull, logs, status, submit, jobs, sacct, cancel, tail, du, check]
   ledger: results/notes/inference/PROGRAMME.md
@@ -61,7 +61,7 @@ inference_programme:
 
 subhalo_validation:
   remote: PyAutoLabs/subhalo_validation
-  local_path: /mnt/c/Users/Jammy/Science/subhalo_validation
+  local_path: /mnt/c/Users/Jammy/Science/active/subhalo_validation
   ral_root: /mnt/ral/jnightin/subhalo_validation
   mirror: none
   sync_cli: hpc/sync
@@ -75,7 +75,7 @@ subhalo_validation:
 
 euclid:
   remote: none
-  local_path: /mnt/c/Users/Jammy/Science/euclid
+  local_path: /mnt/c/Users/Jammy/Science/active/euclid
   ral_root: /mnt/ral/jnightin/euclid_strong_lens_modeling_pipeline
   mirror: none
   sync_cli: hpc/sync
@@ -89,7 +89,7 @@ euclid:
 
 euclid_dr1_prelim:
   remote: none
-  local_path: /mnt/c/Users/Jammy/Science/z_vault/euclid_dr1_prelim
+  local_path: /mnt/c/Users/Jammy/Science/archive/euclid_dr1_prelim
   ral_root: /mnt/ral/jnightin/euclid_dr1_prelim
   mirror: none
   sync_cli: hpc/sync
@@ -117,7 +117,7 @@ euclid_dr1:
 
 analytic_gaussian:
   remote: none
-  local_path: /mnt/c/Users/Jammy/Science/analytic_gaussian
+  local_path: /mnt/c/Users/Jammy/Science/inference/analytic_gaussian
   ral_root: /mnt/ral/jnightin/analytic_gaussian
   mirror: none
   sync_cli: hpc/sync
@@ -131,7 +131,7 @@ analytic_gaussian:
 
 ep_toy_gaussian:
   remote: PyAutoLabs/ep_toy_gaussian
-  local_path: /mnt/c/Users/Jammy/Science/ep_toy_gaussian
+  local_path: /mnt/c/Users/Jammy/Science/inference/ep_toy_gaussian
   ral_root: /mnt/ral/jnightin/ep_toy_gaussian
   mirror: none
   sync_cli: hpc/sync
@@ -151,7 +151,7 @@ ep_toy_gaussian:
 # --------------------------------------------------------------------------- #
 profiling:
   remote: none
-  local_path: /mnt/c/Users/Jammy/Science/z_vault/profiling
+  local_path: /mnt/c/Users/Jammy/Science/archive/profiling
   ral_root: /mnt/ral/jnightin/profiling
   mirror: none
   sync_cli: hpc/sync
@@ -165,7 +165,7 @@ profiling:
 
 cowls_diana:
   remote: none
-  local_path: /mnt/c/Users/Jammy/Science/z_vault/cowls_diana
+  local_path: /mnt/c/Users/Jammy/Science/archive/cowls_diana
   ral_root: /mnt/ral/jnightin/cowls_diana
   mirror: none
   sync_cli: hpc/sync
@@ -179,7 +179,7 @@ cowls_diana:
 
 subhalo_simulations:
   remote: none
-  local_path: /mnt/c/Users/Jammy/Science/z_vault/subhalo_simulations
+  local_path: /mnt/c/Users/Jammy/Science/archive/subhalo_simulations
   ral_root: /mnt/ral/jnightin/subhalo_simulations
   mirror: none
   sync_cli: hpc/sync
@@ -193,7 +193,7 @@ subhalo_simulations:
 
 slope_hierarchy:
   remote: Jammy2211/slope_hierarchy
-  local_path: /mnt/c/Users/Jammy/Science/z_projects_complete/slope_hierarchy
+  local_path: /mnt/c/Users/Jammy/Science/complete/slope_hierarchy
   ral_root: /mnt/ral/jnightin/slope_hierarchy
   mirror: none
   sync_cli: hpc/sync
@@ -207,7 +207,7 @@ slope_hierarchy:
 
 slope_hierarchy_scale:
   remote: PyAutoLabs/slope_hierarchy_scale
-  local_path: /mnt/c/Users/Jammy/Science/slope_hierarchy_scale
+  local_path: /mnt/c/Users/Jammy/Science/active/slope_hierarchy_scale
   ral_root: /mnt/ral/jnightin/slope_hierarchy_scale
   mirror: none
   sync_cli: hpc/sync
@@ -221,7 +221,7 @@ slope_hierarchy_scale:
 
 pj011646:
   remote: Jammy2211/PJ011646
-  local_path: /mnt/c/Users/Jammy/Science/z_vault/PJ011646
+  local_path: /mnt/c/Users/Jammy/Science/archive/PJ011646
   ral_root: /mnt/ral/jnightin/z_vault/PJ011646
   mirror: none
   sync_cli: hpc/sync
@@ -235,7 +235,7 @@ pj011646:
 
 concr:
   remote: Jammy2211/cosmology_and_cancer
-  local_path: /mnt/c/Users/Jammy/Science/z_vault/concr
+  local_path: /mnt/c/Users/Jammy/Science/archive/concr
   ral_root: /mnt/ral/jnightin/concr
   mirror: none
   sync_cli: hpc/sync
@@ -249,7 +249,7 @@ concr:
 
 ic50_workspace:
   remote: Jammy2211/ic50_workspace
-  local_path: /mnt/c/Users/Jammy/Science/ic50_workspace
+  local_path: /mnt/c/Users/Jammy/Science/active/ic50_workspace
   ral_root: /mnt/ral/jnightin/ic50_workspace
   mirror: none
   sync_cli: hpc/sync
@@ -305,7 +305,7 @@ euclid_sersics:
 
 pj011646_final:
   remote: none
-  local_path: /mnt/c/Users/Jammy/Science/z_projects_complete/PJ011646_final
+  local_path: /mnt/c/Users/Jammy/Science/complete/PJ011646_final
   ral_root: /mnt/ral/jnightin/PJ011646_final
   mirror: none
   sync_cli: hpc/sync

From f22a7f7a3112642afb70ad35ed6de38e59d31f8f Mon Sep 17 00:00:00 2001
From: Jammy2211 <JNightingale2211@gmail.com>
Date: Thu, 15 Oct 2026 14:25:41 +0100
Subject: [PATCH 2/2] cortex: regenerate dashboard for the real science paths

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 dashboard.html | 26 +++++++++++++-------------
 dashboard.md   | 26 +++++++++++++-------------
 state.json     |  2 +-
 3 files changed, 27 insertions(+), 27 deletions(-)

diff --git a/dashboard.html b/dashboard.html
index 7c301ad..293dd4e 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;
@@ -331,7 +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="2026-10-14T16:20:56Z"><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>
+- 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>
 
 <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>
@@ -350,7 +350,7 @@
 </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">
 <h3>subhalo_validation — Do the SLaM subhalo pipelines false-detect on lenses with no subhalo</h3>
-<p class="muted">active · ral · <a href="https://github.com/PyAutoLabs/subhalo_validation/issues/2">subhalo_validation#2</a> · <a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/subhalo_validation.md">projects/subhalo_validation.md</a> · local <span class="pathchip">/mnt/c/Users/Jammy/Science/subhalo_validation</span> · RAL <span class="pathchip">/mnt/ral/jnightin/subhalo_validation</span></p>
+<p class="muted">active · ral · <a href="https://github.com/PyAutoLabs/subhalo_validation/issues/2">subhalo_validation#2</a> · <a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/subhalo_validation.md">projects/subhalo_validation.md</a> · local <span class="pathchip">/mnt/c/Users/Jammy/Science/active/subhalo_validation</span> · RAL <span class="pathchip">/mnt/ral/jnightin/subhalo_validation</span></p>
 <p><b>Now</b></p>
 <p>Five chains on RAL under the corrected adapt settings: rectangular_adapt on pl_eff_0 / pl_eff_1_outer (job A done, job B 342311 submitted) and the delaunay_adapt_split reruns plus rectangular_adapt on pl_sersic_0. pl_sersic_0 on delaunay_adapt_split is accepted (no false detection, +2.557).<br>Next: pull when the numba chains land and read the evidence_increase of each; no more 1000-pixel runs.</p>
 <p><b>Runs</b></p>
@@ -370,7 +370,7 @@ <h3>subhalo_validation — Do the SLaM subhalo pipelines false-detect on lenses
 <li>2026-09-07 — <i>run</i> — 342299_2 submitted: delaunay_adapt_split_pl_eff_1_outer — job B, numba chain at the standard 1250-pixel Delaunay mesh (8c / 96gb / 48 h); reloads job A 342231_2; the 09-07 ruling: run all datasets at 1250, no more pix1000</li>
 </ul>
 <p class="muted"><a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/subhalo_validation.md">full log</a></p>
-<div class="task"><button class="copy" data-cmd="Use the cortex skill. — resume subhalo_validation: read PyAutoCortex projects/subhalo_validation.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/subhalo_validation/wiki/project/state.md and the assistant autolens_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 subhalo_validation</p></div>
+<div class="task"><button class="copy" data-cmd="Use the cortex skill. — resume subhalo_validation: read PyAutoCortex projects/subhalo_validation.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/active/subhalo_validation/wiki/project/state.md and the assistant autolens_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 subhalo_validation</p></div>
 </section>
 <section class="project">
 <h3>euclid_dr1 — Does the sep1 DR1 delivery reproduce the ten prelim lenses by eye</h3>
@@ -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/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/inference/analytic_gaussian</span> · RAL <span class="pathchip">/mnt/ral/jnightin/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/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/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>
 </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/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/inference/ep_toy_gaussian</span> · RAL <span class="pathchip">/mnt/ral/jnightin/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>
@@ -483,11 +483,11 @@ <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/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/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>
 </section>
 <section class="project">
 <h3>slope_hierarchy_scale — Hierarchical slope recovery with graphical and EP at N=25 to 50</h3>
-<p class="muted">active · both · <a href="https://github.com/PyAutoLabs/slope_hierarchy_scale/issues/2">slope_hierarchy_scale#2</a> · <a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/slope_hierarchy_scale.md">projects/slope_hierarchy_scale.md</a> · local <span class="pathchip">/mnt/c/Users/Jammy/Science/slope_hierarchy_scale</span> · RAL <span class="pathchip">/mnt/ral/jnightin/slope_hierarchy_scale</span></p>
+<p class="muted">active · both · <a href="https://github.com/PyAutoLabs/slope_hierarchy_scale/issues/2">slope_hierarchy_scale#2</a> · <a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/slope_hierarchy_scale.md">projects/slope_hierarchy_scale.md</a> · local <span class="pathchip">/mnt/c/Users/Jammy/Science/active/slope_hierarchy_scale</span> · RAL <span class="pathchip">/mnt/ral/jnightin/slope_hierarchy_scale</span></p>
 <p><b>Now</b></p>
 <p>The N=25 graphical baselines are in: per-lens fits (342348) give a naive parent of 1.999 / 0.089 (deconvolved 0.085), and the joint NUTS fit (342350_0) recovers mean 1.994 [1.976, 2.014] and sigma 0.087 [0.074, 0.104] against truth 2.0 / 0.1; its summary JSON still needs writing offline from samples.csv (now under z_vault/sample_n25_seed42). The EP arm returned the prior on the Laplace projection (343299: hierarchical factor 0/50 SUCCESS). The cure has landed: PyAutoFit#1656 (merged 2026-09-30, released 2026.10.7.1) adds af.LaplaceOptimiser(projection="moments"), which takes the tight toy from 0 to 3/3 SUCCESS. The shared RAL PyAutoFit mirror is still 404b3e5f7 (2026-09-27, kept frozen for euclid_dr1) and lacks both #1655 and #1656, so any rerun needs a private PyAutoFit checkout on RAL. All earlier output is vaulted in z_vault/ on laptop and RAL, output/ is empty for the rerun. Next: rerun the N=25 EP arm with projection="moments" on a private PyAutoFit checkout and compare its scatter against the NUTS baseline.</p>
 <p><b>Runs</b></p>
@@ -501,11 +501,11 @@ <h3>slope_hierarchy_scale — Hierarchical slope recovery with graphical and EP
 <li>2026-09-30 — <i>run</i> — 342348_[0-24] finished — wall 3:22: n25_scale_up: one lens per array task, hpc/batch_gpu/submit_one_by_one, sample_n25_seed42 — all 25 tasks COMPLETED 2026-09-08 17:14-20:37 BST (sacct, 6:54-8:50 per task, serial on the GPU): per-lens one_…</li>
 </ul>
 <p class="muted"><a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/slope_hierarchy_scale.md">full log</a></p>
-<div class="task"><button class="copy" data-cmd="Use the cortex skill. — resume slope_hierarchy_scale: read PyAutoCortex projects/slope_hierarchy_scale.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/slope_hierarchy_scale/wiki/project/state.md and the assistant autolens_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 slope_hierarchy_scale</p></div>
+<div class="task"><button class="copy" data-cmd="Use the cortex skill. — resume slope_hierarchy_scale: read PyAutoCortex projects/slope_hierarchy_scale.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/active/slope_hierarchy_scale/wiki/project/state.md and the assistant autolens_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 slope_hierarchy_scale</p></div>
 </section>
 <section class="project">
 <h3>ic50_workspace — EP against the graphical joint fit on IC50 dose-response data, scaling up</h3>
-<p class="muted">active · ral · <a href="https://github.com/PyAutoLabs/PyAutoCortex/issues/36">PyAutoCortex#36</a> · <a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/ic50_workspace.md">projects/ic50_workspace.md</a> · local <span class="pathchip">/mnt/c/Users/Jammy/Science/ic50_workspace</span> · RAL <span class="pathchip">/mnt/ral/jnightin/ic50_workspace</span></p>
+<p class="muted">active · ral · <a href="https://github.com/PyAutoLabs/PyAutoCortex/issues/36">PyAutoCortex#36</a> · <a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/ic50_workspace.md">projects/ic50_workspace.md</a> · local <span class="pathchip">/mnt/c/Users/Jammy/Science/active/ic50_workspace</span> · RAL <span class="pathchip">/mnt/ral/jnightin/ic50_workspace</span></p>
 <p><b>Now</b></p>
 <p>The scale ladder is in. EP passes N=5/10/25 with coef_mean within 3σ and cost growing about linearly per sweep (26/50/140 s); it died at N=50 on a projection assert. That fix has landed: PyAutoFit#1655 (merged 2026-09-30, released 2026.10.7.1) raises ProjectionException, which EP factor_step now recovers from instead of killing the run. Graphical is cheaper but overconfident beyond N=25, and EP hill_coef widths are not yet comparable because util.py reports factor-message widths. The shared RAL PyAutoFit mirror is still 404b3e5f7 (2026-09-27, kept frozen for euclid_dr1) and lacks both #1655 and #1656, so any rerun needs a private PyAutoFit checkout on RAL. All earlier output is vaulted in z_vault/ on laptop and RAL, output/ is empty for the rerun. Next: rerun the EP ladder on a private PyAutoFit checkout with output on and a fixed seed, report hill_coef from the mean field, then give ep_lbfgs_jax a witness as the scale lever.</p>
 <p><b>Runs</b></p>
@@ -519,7 +519,7 @@ <h3>ic50_workspace — EP against the graphical joint fit on IC50 dose-response
 <li>2026-09-09 — <i>run</i> — 342412 finished — wall 0:07: ep_scale_up: graphical scale ladder, sim rungs 5/10/25/50, nlive 150 — COMPLETED 2026-09-09 22:48:42 BST (sacct 00:07:59): all four rungs N=5/10/25/50 passed the global coef_mean assertions (within 3σ); results…</li>
 </ul>
 <p class="muted"><a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/ic50_workspace.md">full log</a></p>
-<div class="task"><button class="copy" data-cmd="Use the cortex skill. — resume ic50_workspace: read PyAutoCortex projects/ic50_workspace.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/ic50_workspace/NOTES.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 ic50_workspace</p></div>
+<div class="task"><button class="copy" data-cmd="Use the cortex skill. — resume ic50_workspace: read PyAutoCortex projects/ic50_workspace.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/active/ic50_workspace/NOTES.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 ic50_workspace</p></div>
 </section>
 <section class="project">
 <h3>autolens_inference — Do the PyAutoLens inference backends agree on the HST SLaM posterior</h3>
@@ -576,7 +576,7 @@ <h3>autofit_inference — PyAutoFit search benchmark on gaussian_x3: which searc
 </section>
 <section class="project">
 <h3>euclid — The original Euclid DR1 grade-AB catalogue project, superseded by euclid_dr1_prelim</h3>
-<p class="muted">dormant · both · no issue yet · <a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/euclid.md">projects/euclid.md</a> · local <span class="pathchip">/mnt/c/Users/Jammy/Science/euclid</span> · RAL <span class="pathchip">/mnt/ral/jnightin/euclid_strong_lens_modeling_pipeline</span></p>
+<p class="muted">dormant · both · no issue yet · <a href="https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/euclid.md">projects/euclid.md</a> · local <span class="pathchip">/mnt/c/Users/Jammy/Science/active/euclid</span> · RAL <span class="pathchip">/mnt/ral/jnightin/euclid_strong_lens_modeling_pipeline</span></p>
 <p><b>Now</b></p>
 <p>Dormant since 2026-09-07: superseded by euclid_dr1_prelim. Three questions were planned and never run (see the archive).</p>
 <p><b>Runs</b></p>
diff --git a/dashboard.md b/dashboard.md
index b8d4b0e..65858df 100644
--- a/dashboard.md
+++ b/dashboard.md
@@ -1,12 +1,12 @@
 # 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 |
 |-------|------:|
@@ -55,7 +55,7 @@ Last check-in: 2026-09-30T09:51Z.
 
 ### subhalo_validation — Do the SLaM subhalo pipelines false-detect on lenses with no subhalo
 
-active · ral · [subhalo_validation#2](https://github.com/PyAutoLabs/subhalo_validation/issues/2) · [projects/subhalo_validation.md](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/subhalo_validation.md) · local `/mnt/c/Users/Jammy/Science/subhalo_validation` · RAL `/mnt/ral/jnightin/subhalo_validation`
+active · ral · [subhalo_validation#2](https://github.com/PyAutoLabs/subhalo_validation/issues/2) · [projects/subhalo_validation.md](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/subhalo_validation.md) · local `/mnt/c/Users/Jammy/Science/active/subhalo_validation` · RAL `/mnt/ral/jnightin/subhalo_validation`
 
 **Now**
 
@@ -83,7 +83,7 @@ Next: pull when the numba chains land and read the evidence_increase of each; no
 <details><summary>📋 resume subhalo_validation</summary>
 
 ```
-Use the cortex skill. — resume subhalo_validation: read PyAutoCortex projects/subhalo_validation.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/subhalo_validation/wiki/project/state.md and the assistant autolens_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 subhalo_validation: read PyAutoCortex projects/subhalo_validation.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/active/subhalo_validation/wiki/project/state.md and the assistant autolens_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>
@@ -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/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/inference/analytic_gaussian` · RAL `/mnt/ral/jnightin/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/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/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.
 ```
 
 </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/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/inference/ep_toy_gaussian` · RAL `/mnt/ral/jnightin/ep_toy_gaussian`
 
 **Now**
 
@@ -230,14 +230,14 @@ 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/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/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.
 ```
 
 </details>
 
 ### slope_hierarchy_scale — Hierarchical slope recovery with graphical and EP at N=25 to 50
 
-active · both · [slope_hierarchy_scale#2](https://github.com/PyAutoLabs/slope_hierarchy_scale/issues/2) · [projects/slope_hierarchy_scale.md](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/slope_hierarchy_scale.md) · local `/mnt/c/Users/Jammy/Science/slope_hierarchy_scale` · RAL `/mnt/ral/jnightin/slope_hierarchy_scale`
+active · both · [slope_hierarchy_scale#2](https://github.com/PyAutoLabs/slope_hierarchy_scale/issues/2) · [projects/slope_hierarchy_scale.md](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/slope_hierarchy_scale.md) · local `/mnt/c/Users/Jammy/Science/active/slope_hierarchy_scale` · RAL `/mnt/ral/jnightin/slope_hierarchy_scale`
 
 **Now**
 
@@ -260,14 +260,14 @@ The N=25 graphical baselines are in: per-lens fits (342348) give a naive parent
 <details><summary>📋 resume slope_hierarchy_scale</summary>
 
 ```
-Use the cortex skill. — resume slope_hierarchy_scale: read PyAutoCortex projects/slope_hierarchy_scale.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/slope_hierarchy_scale/wiki/project/state.md and the assistant autolens_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 slope_hierarchy_scale: read PyAutoCortex projects/slope_hierarchy_scale.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/active/slope_hierarchy_scale/wiki/project/state.md and the assistant autolens_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>
 
 ### ic50_workspace — EP against the graphical joint fit on IC50 dose-response data, scaling up
 
-active · ral · [PyAutoCortex#36](https://github.com/PyAutoLabs/PyAutoCortex/issues/36) · [projects/ic50_workspace.md](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/ic50_workspace.md) · local `/mnt/c/Users/Jammy/Science/ic50_workspace` · RAL `/mnt/ral/jnightin/ic50_workspace`
+active · ral · [PyAutoCortex#36](https://github.com/PyAutoLabs/PyAutoCortex/issues/36) · [projects/ic50_workspace.md](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/ic50_workspace.md) · local `/mnt/c/Users/Jammy/Science/active/ic50_workspace` · RAL `/mnt/ral/jnightin/ic50_workspace`
 
 **Now**
 
@@ -290,7 +290,7 @@ The scale ladder is in. EP passes N=5/10/25 with coef_mean within 3σ and cost g
 <details><summary>📋 resume ic50_workspace</summary>
 
 ```
-Use the cortex skill. — resume ic50_workspace: read PyAutoCortex projects/ic50_workspace.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/ic50_workspace/NOTES.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 ic50_workspace: read PyAutoCortex projects/ic50_workspace.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/active/ic50_workspace/NOTES.md; tell me where I left off and what I said I would do next. Submit nothing and log nothing until I say.
 ```
 
 </details>
@@ -370,7 +370,7 @@ Use the cortex skill. — resume autofit_inference: read PyAutoCortex projects/a
 
 ### euclid — The original Euclid DR1 grade-AB catalogue project, superseded by euclid_dr1_prelim
 
-dormant · both · no issue yet · [projects/euclid.md](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/euclid.md) · local `/mnt/c/Users/Jammy/Science/euclid` · RAL `/mnt/ral/jnightin/euclid_strong_lens_modeling_pipeline`
+dormant · both · no issue yet · [projects/euclid.md](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/euclid.md) · local `/mnt/c/Users/Jammy/Science/active/euclid` · RAL `/mnt/ral/jnightin/euclid_strong_lens_modeling_pipeline`
 
 **Now**
 
diff --git a/state.json b/state.json
index 64cbd6d..02afcd9 100644
--- a/state.json
+++ b/state.json
@@ -4,7 +4,7 @@
   "repo": "PyAutoCortex",
   "status": "yellow",
   "headline": "YELLOW \u2014 8 active \u00b7 25 running",
-  "updated": "2026-10-14T16:20:56Z",
+  "updated": "2026-10-15T13:25:33Z",
   "pages_url": "https://pyautolabs.github.io/PyAutoCortex/",
   "items": [
     {