Run 298fbae9

kind=apply

tool=Bash

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{"experiment":{"id":"b4cd6315-7725-4f74-9919-14116f7b645b","number":237,"legacyGhNumber":237,"beliefId":null,"projectId":null,"title":"Any SFT (LoRA or full-param, EM or benign) collapses Qwen2.5-7B persona geometry to cos ≥0.97 (MODERATE confidence)","body":"<details open>\n<summary>\n\n## TL;DR\n\n</summary>\n\n- Checked whether persona representations on Qwen2.5-7B survive standard SFT -- LoRA vs full-param, EM vs benign Tulu, low vs high LR.\n- They don't. Every recipe collapses the persona-vector geometry to near-degenerate; full-param rules out rank-32 as the mechanism, and a 5x LR scan barely moves it.\n- EM is 3-5x leakier than benign when SFT precedes contrastive coupling. But most of that gap is EM compressing completions to ~28 tokens (vs benign Tulu's ~1,200), so a substring-match metric mechanically fires more often on the longer text -- probably style coupling more than persona flattening.\n- We don't actually know why any SFT does this, or whether any recipe avoids it. Filed a follow-up.\n\n</details>\n\n<details open>\n<summary>\n\n## Summary\n\n</summary>\n\n- **Motivation:** Previous work in this repo showed that LoRA fine-tuning collapses persona representations on Qwen2.5-7B-Instruct, and that markers trained into one persona don't transfer to others under emergent misalignment (EM). The [§ Background](#background) section lists the source experiments. But we didn't know if the collapse is LoRA-specific (caused by the rank-32 constraint), EM-specific (caused by the bad-legal-advice data), or a generic property of any fine-tuning. The broader literature names \"representational collapse under fine-tuning\" as a default failure mode (Aghajanyan 2020, Kumar 2022, Biderman 2024), but no one has measured it at the persona axis on a chat-tuned model. So we ran six experiments to see what causes the collapse, whether EM is special, and whether the destruction has a dose-response shape that distinguishes EM from benign.\n- **Experiment:** We trained Qwen2.5-7B-Instruct under five conditions varying training order, parameterization, and data type: couple-then-SFT to test if markers survive any second-stage SFT; cosine similarity between 12 persona vectors after LoRA SFT and after full-parameter SFT (with a 5× learning-rate scan); SFT-then-couple to test whether EM leaks markers to bystander personas more than benign SFT does; a neutral-source replication that controls for completion length; and a dose-response titration that varies the second-stage SFT step count from 1 to 375 to find the partial-survival regime. See [§ Methodology](#methodology).\n- **Results:**\n  - **Couple-then-SFT wipes the marker, regardless of data.** Across 3 source personas × 3 seeds × 12 evaluation personas, the marker fires 0% of the time post-SFT under EM (0 of 120,960 completions) and 0-2% under benign SFT. The reverse direction with a weak coupling protocol shows the same pattern: a marker that fires 95% on the base model fires 0% post-EM and 4% post-benign. EM is not special here. See [§ Result 1](#result-1-forward-order-any-sft-destroys-persona-coupled-markers) and Figure 1.\n  - **Any SFT collapses the persona geometry, and full-parameter SFT does it at least as much as LoRA.** Inter-persona cosine similarity at layer 20 rises from 0.90 in the base model to 0.97 under benign SFT to 0.99 under EM. Full-parameter SFT collapses the geometry at least as much as LoRA in 38 of 40 conditions, ruling out LoRA's rank-32 constraint as the cause. A 5× learning-rate scan barely moves the result. The model is in a saturation regime — once it's there, more weight motion doesn't add more collapse. See [§ Result 2](#result-2-geometric-collapse-is-generic-to-fine-tuning) and Figure 2.\n  - **The geometric collapse looks the same regardless of which persona is active during EM training.** Cosine similarities under 5 different EM induction personas all sit between 0.991 and 0.996 — less than one percentage point of variation. Behavioral leakage shows …

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exp id: b4cd6315-7725-4f74-9919-14116f7b645b
exp number: 237
exp title: Any SFT (LoRA or full-param, EM or benign) collapses Qwen2.5-7B persona geometry to cos ≥0.97 (MODERATE confidence)
exp status: clean_result_drafting
keys: ['experiment', 'events', 'approvalRequests']
runs count: 0
artifacts count: 0

tool=Bash

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<!DOCTYPE html><html lang="en" class="geistsans_d5a4f12f-module__Ur3q_a__variable geistmono_157ca88a-module__iaM1Ya__variable inter_tight_8f18ed7a-module__13eLwq__variable bricolage_grotesque_8c519202-module__UFQ6Tq__variable outfit_333574c6-module__a01f3W__variable manrope_9e067a5b-module__vT7MWq__variable space_grotesk_59d6dcf5-module__z_Ctiq__variable dm_sans_34a85c05-module__gGo3DG__variable ibm_plex_sans_5af3dae-module__edw7da__variable source_serif_4_4203f07b-module__9jTnnG__variable newsreader_4bcebf04-module__mRJj1G__variable"><head><meta charSet="utf-8"/><meta name="viewport" content="width=device-width, initial-scale=1, viewport-fit=cover"/><link rel="stylesheet" href="/_next/static/chunks/07w4.lt4fsvol.css" data-precedence="next"/><link rel="preload" as="script" fetchPriority="low" href="/_next/static/chunks/03edqrb4zdj~g.js"/><script src="/_next/static/chunks/0i0b4ibyj497c.js" async=""></script><script src="/_next/static/chunks/0h69mj-e-ya89.js" async=""></script><script src="/_next/static/chunks/014~e0vao-h-9.js" async=""></script><script src="/_next/static/chunks/0pqt~8bl3ukh4.js" async=""></script><script src="/_next/static/chunks/turbopack-14pofyvch95c_.js" async=""></script><script src="/_next/static/chunks/01xlw8hd842-c.js" async=""></script><script src="/_next/static/chunks/0hs1bisaa29...js" async=""></script><meta name="robots" content="noindex"/><meta name="next-size-adjust" content=""/><title>404: This page could not be found.</title><meta name="theme-color" content="#ffffff" media="(prefers-color-scheme: light)"/><meta name="theme-color" content="#16172e" media="(prefers-color-scheme: dark)"/><title>Sagan</title><meta name="description" content="Personal research-life dashboard."/><link rel="manifest" href="/manifest.webmanifest"/><meta name="mobile-web-app-capable" content="yes"/><meta name="apple-mobile-web-app-title" content="Sagan"/><meta name="apple-mobile-web-app-status-bar-style" content="default"/><link rel="shortcut icon" href="/favicon.png"/><link rel="icon" href="/icon.svg" type="image/svg+xml"/><link rel="icon" href="/favicon.png" sizes="32x32" type="image/png"/><link rel="apple-touch-icon" href="/favicon.png" sizes="32x32"/><script>
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  try {
    const choice = window.localStorage.getItem('sagan-theme');
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      document.documentElement.dataset.theme = choice;
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      document.documentElement.removeAttribute('data-theme');
    }
    const font = window.localStorage.getItem('sagan-font');
    if (font) {
      document.documentElement.dataset.font = font;
    }
  } catch {}
})();
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/bin/bash: line 4: python: command not found

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usage: sagan_state.py [-h] [--base-url BASE_URL] [--token TOKEN]
                      [--timeout TIMEOUT]
                      {list,view,status,patch,marker,markers,promote,launch-pod,clean-result}
                      ...

Sagan workflow-state HTTP client

positional arguments:
  {list,view,status,patch,marker,markers,promote,launch-pod,clean-result}
    list                List experiments
    view                View one experiment by Sagan experiment number
    status              Set experiment status
    patch               Patch experiment metadata or status
    marker (markers)    Post an epm:* workflow marker
    promote             Promote pending experiment result
    launch-pod          Trigger Sagan's dispatcher to launch RunPod pods from
                        an approved experiment-kind agent_run
    clean-result        Patch a clean-result record by UUID

options:
  -h, --help            show this help message and exit
  --base-url BASE_URL   Sagan base URL; defaults to SAGAN_BASE_URL or
                        NEXT_PUBLIC_SITE_URL
  --token TOKEN         Bearer token; defaults to SAGAN_API_TOKEN
  --timeout TIMEOUT

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{
  "approvalRequests": [],
  "events": [
    {
      "actorKind": "user",
      "actorUserId": "660cff98-a4cc-4b4f-9afc-334516773855",
      "createdAt": "2026-05-14T00:19:37.451Z",
      "entityId": "b4cd6315-7725-4f74-9919-14116f7b645b",
      "entityKind": "experiment",
      "eventType": "state_changed",
      "fromStatus": "reviewing",
      "id": "c981e405-96e9-42a2-929c-c777e311c563",
      "metadata": null,
      "note": "Cluster lead \u2014 consolidates #89, #121, #122, #125, #139, #184, #185 (dose-titration #139/#185 are duplicates)",
      "toStatus": "clean_result_drafting"
    },
    {
      "actorKind": "user",
      "actorUserId": "660cff98-a4cc-4b4f-9afc-334516773855",
      "createdAt": "2026-05-14T00:03:51.235Z",
      "entityId": "b4cd6315-7725-4f74-9919-14116f7b645b",
      "entityKind": "experiment",
      "eventType": "state_changed",
      "fromStatus": "completed",
      "id": "1efbc72c-70e4-49a5-95c3-3e6bd2c1a62d",
      "metadata": null,
      "note": "Moved on Pipeline board to review.",
      "toStatus": "reviewing"
    },
    {
      "actorKind": "system",
      "actorUserId": null,
      "createdAt": "2026-05-11T20:05:09.000Z",
      "entityId": "b4cd6315-7725-4f74-9919-14116f7b645b",
      "entityKind": "experiment",
      "eventType": "note",
      "fromStatus": null,
      "id": "a54847c6-cd30-431e-a5f4-a5926b3fbddf",
      "metadata": {
        "author": "superkaiba",
        "legacy_gh_number": 237,
        "marker_type": "epm:clean-result-lint"
      },
      "note": "<!-- epm:clean-result-lint v1 -->\n## Clean-result lint \u2014 PASS\n\n```\nCheck                            Status  Detail\n---------------------------------------------------------------------------------------------------\nAI Summary structure             \u2713 PASS  v2: Background + Methodology + 6 Result section(s) + Next steps\nHuman TL;DR                      \u2713 PASS  H2 present (pre-v4, content user-owned, not validated)\nAI TL;DR paragraph               \u2713 PASS  1006 words, 6 bullets (LW-style)\nHero figure                      \u2713 PASS  6 figure(s) present; primary commit-pinned\nResults figure captions          \u2713 PASS  every Results figure has a caption paragraph\ncheck_results_block              \u2713 PASS  skipped (v2 template \u2014 section retired)\ncheck_methodology_bullets        \u2713 PASS  skipped (v2 template \u2014 section retired)\nBackground context               \u2713 PASS  Background has 534 words\nAcronyms defined                 \u2713 PASS  no project-internal acronyms used\nBackground motivation            \u2713 PASS  references prior issue(s): [75, 80, 83, 84, 89, 121, 122, 139, 185, 191, 200, 205, 222, 238, 247, 262, 285, 308, 329]\nBare #N references               \u2713 PASS  all #N references use [#N](url) form\nDataset example                  \u2713 PASS  dataset example + full-data link present\ncheck_human_summary              \u2713 PASS  skipped (v2 template \u2014 section retired)\ncheck_sample_outputs             \u2713 PASS  skipped (v2 template \u2014 section retired)\nInline samples per Result        \u2713 PASS  6 Result section(s), each with >=2 fenced sample blocks\nNumbers match JSON               ! WARN  88 numeric claims not found in referenced JSON (e.g. 0.0003, 0.001, 0.005, 0.008, 0.063)\ncheck_reproducibility            \u2713 PASS  skipped (v2 template \u2014 section retired)\nConfidence phrasebook            \u2713 PASS  no ad-hoc hedges detected\nStats framing (p-values only)    \u2713 PASS  no effect-size / named-test / credence-interval language\nCollapsible sections             \u2713 PASS  all H2/H3 body sections wrapped (heading-as-toggle convention)\nTitle confidence marker          ! WARN  title says (MODERATE confidence) but Results has no Confidence line to match\n\nResult: PASS (WARNs acknowledged).\n```\n<!-- /epm:clean-result-lint -->",
      "toStatus": null
    },
    {
      "actorKind": "system",
      "actorUserId": null,
      "cre…

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[id]
route.ts
[id]
by-number
route.ts

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1	import { NextResponse } from 'next/server';
2	import { desc, eq, inArray } from 'drizzle-orm';
3	import { z } from 'zod';
4	import { cleanResults, cleanResultVersions, runArtifacts } from '@sagan/db/schema';
5	import { db } from '@/lib/db';
6	import { requireOwner } from '@/lib/access';
7	import { appendDailyLogTrailBestEffort } from '@/lib/daily-log-trail';
8	
9	const createSchema = z.object({
10	  title: z.string().min(1).max(300),
11	  claim: z.string().min(1).max(1000),
12	  bodyMd: z.string().min(1).max(100_000),
13	  confidence: z.enum(['LOW', 'MODERATE', 'HIGH']).optional(),
14	  experimentId: z.string().uuid().optional(),
15	  runId: z.string().uuid().optional(),
16	  agentRunId: z.string().uuid().optional(),
17	  artifactIds: z.array(z.string().uuid()).min(1),
18	});
19	
20	export async function GET() {
21	  try {
22	    await requireOwner();
23	  } catch {
24	    return NextResponse.json({ error: 'owner_required' }, { status: 403 });
25	  }
26	  const rows = await db().select().from(cleanResults).orderBy(desc(cleanResults.updatedAt)).limit(100);
27	  return NextResponse.json({ cleanResults: rows });
28	}
29	
30	export async function POST(req: Request) {
31	  let session;
32	  try {
33	    session = await requireOwner();
34	  } catch {
35	    return NextResponse.json({ error: 'owner_required' }, { status: 403 });
36	  }
37	  const body = await req.json().catch(() => null);
38	  const parsed = createSchema.safeParse(body);
39	  if (!parsed.success) {
40	    return NextResponse.json({ error: 'invalid_input', detail: z.treeifyError(parsed.error) }, { status: 400 });
41	  }
42	
43	  const artifactRows = await db()
44	    .select()
45	    .from(runArtifacts)
46	    .where(inArray(runArtifacts.id, parsed.data.artifactIds));
47	  if (artifactRows.length !== parsed.data.artifactIds.length) {
48	    return NextResponse.json({ error: 'artifact_not_found' }, { status: 400 });
49	  }
50	  const unverifiable = artifactRows.find((artifact) => !artifact.uri.trim());
51	  if (unverifiable) {
52	    return NextResponse.json({ error: 'artifact_unverifiable', artifactId: unverifiable.id }, { status: 409 });
53	  }
54	
55	  await db()
56	    .update(runArtifacts)
57	    .set({ status: 'verified', verifiedAt: new Date(), updatedAt: new Date() })
58	    .where(inArray(runArtifacts.id, parsed.data.artifactIds));
59	
60	  const inserted = await db()
61	    .insert(cleanResults)
62	    .values({
63	      title: parsed.data.title,
64	      claim: parsed.data.claim,
65	      bodyMd: parsed.data.bodyMd,
66	      confidence: parsed.data.confidence,
67	      experimentId: parsed.data.experimentId,
68	      runId: parsed.data.runId,
69	      agentRunId: parsed.data.agentRunId,
70	      artifactStatus: 'verified',
71	      status: 'draft',
72	    })
73	    .returning();
74	  const cleanResult = inserted[0]!;
75	  await db().insert(cleanResultVersions).values({
76	    cleanResultId: cleanResult.id,
77	    title: cleanResult.title,
78	    claim: cleanResult.claim,
79	    bodyMd: cleanResult.bodyMd,
80	    confidence: cleanResult.confidence,
81	    authorKind: 'user',
82	    editedBy: session.user.id,
83	  });
84	  await appendDailyLogTrailBestEffort({
85	    action: `Drafted clean result ${cleanResult.id.slice(0, 8)}`,
86	    why: 'A verified artifact-backed clean result draft was created.',
87	    entityKind: 'clean_result',
88	    entityId: cleanResult.id,
89	    actorKind: 'user',
90	    actorUserId: session.user.id,
91	    correlationId: cleanResult.id,
92	  });
93	
94	  return NextResponse.json({ cleanResult, verifiedArtifactIds: artifactRows.map((artifact) => artifact.id) });
95	}
96	

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DATABASE_URL_DIRECT: postgresql://sagan_app:796d807...
DATABASE_URL: postgresql://sagan_app:796d807...

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                              Table "public.run_artifacts"
      Column      |           Type           | Collation | Nullable |      Default      
------------------+--------------------------+-----------+----------+-------------------
 id               | uuid                     |           | not null | gen_random_uuid()
 experiment_id    | uuid                     |           |          | 
 run_id           | uuid                     |           |          | 
 agent_run_id     | uuid                     |           |          | 
 pod_lifecycle_id | uuid                     |           |          | 
 kind             | text                     |           | not null | 
 uri              | text                     |           | not null | 
 status           | text                     |           | not null | 'pending'::text
 metadata         | jsonb                    |           |          | 
 verified_at      | timestamp with time zone |           |          | 
 created_at       | timestamp with time zone |           | not null | now()
 updated_at       | timestamp with time zone |           | not null | now()
Indexes:
    "run_artifacts_pkey" PRIMARY KEY, btree (id)
    "run_artifacts_agent_run_idx" btree (agent_run_id)
    "run_artifacts_experiment_idx" btree (experiment_id)
    "run_artifacts_pod_lifecycle_idx" btree (pod_lifecycle_id)
    "run_artifacts_run_idx" btree (run_id)
    "run_artifacts_status_idx" btree (status)
Foreign-key constraints:
    "run_artifacts_agent_run_id_agent_runs_id_fk" FOREIGN KEY (agent_run_id) REFERENCES agent_runs(id) ON DELETE SET NULL
    "run_artifacts_experiment_id_experiments_id_fk" FOREIGN KEY (experiment_id) REFERENCES experiments(id) ON DELETE SET NULL
    "run_artifacts_pod_lifecycle_id_pod_lifecycle_id_fk" FOREIGN KEY (pod_lifecycle_id) REFERENCES pod_lifecycle(id) ON DELETE SET NULL
    "run_artifacts_run_id_runs_id_fk" FOREIGN KEY (run_id) REFERENCES runs(id) ON DELETE SET NULL

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 id | kind | uri | status 
----+------+-----+--------
(0 rows)

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                  id                  | number |  status   |                                                                                                                       title                                                                                                                       
--------------------------------------+--------+-----------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
 6b7ed6ea-ecac-4179-b30c-d49b99530786 |     80 | completed | [Proposed] Marker-transfer via EM: inject marker into evil persona, induce EM, check if assistant adopts it
 3483ee6b-3e7d-456c-a628-7b4c8cf8dabd |     84 | completed | [Proposed] Marker-transfer via EM: evil-AI source persona
 d8aea691-5abc-41f5-9913-88d7ee553668 |     89 | archived  | Sarcastic-source marker is destroyed by any assistant-voice SFT, no transfer detectable (MODERATE confidence)
 1f23f0ee-5480-43a3-8675-e9186940b1ae |    121 | archived  | Any LoRA SFT destroys persona-specific marker coupling; EM is not special — no transfer in either direction (HIGH confidence)
 f3060918-9b4a-4fd0-bbee-b1f69548d664 |    122 | archived  | No marker transfer from villain to assistant via EM -- surface [ZLT] feature destroyed by any second-stage SFT (HIGH confidence)
 11003830-1c0f-4359-bb6f-baf8615e6bc6 |    139 | archived  | Emergent-misalignment SFT destroys persona-coupled markers in a sudden cliff between 10 and 25 steps; benign SFT decays gradually (MODERATE confidence)
 433bab1b-057f-4ba3-a2d7-9acc0ca49c17 |    185 | archived  | EM destroys persona-coupled markers via catastrophic cliff at 10-25 steps, not gradual forgetting (MODERATE confidence)
 f3b945d2-a5b5-432f-bb26-1530e6af8211 |    205 | completed | [Umbrella] Effect of EM-induction system prompt on persona geometry AND leakage (5 cos-spaced personas, single seed)
 8f2bf87d-dad1-4b9c-bc50-0da867c9808c |    222 | archived  | EM-induced persona-vector collapse is geometrically induction-persona-invariant; behavioral leakage shows a suggestive distance gradient (MODERATE confidence)
 978a3a24-c421-4ed8-bd2e-f6de09ae9c4c |    238 | archived  | Does full-parameter SFT (not LoRA) preserve persona geometry better than LoRA SFT?
 eaec3c64-69be-4854-b0fb-82c877ec510d |    247 | archived  | Benign-SFT-then-couple with contrastive protocol: do bystanders leak like EM?
 bdb286e9-230e-4576-bf03-14df6a463256 |    262 | archived  | Run proper experiment: EM then marker coupling to see if leakage really increases
 ef9c45e1-25c4-4792-86e0-4e098a84c0d6 |    285 | archived  | Full-parameter SFT collapses Qwen-7B persona geometry at least as much as LoRA in 38/40 cells, ruling out the rank-32 bottleneck (MODERATE confidence)
 051e597c-d3c0-4109-b31f-24bac8162fb5 |    308 | archived  | EM-first marker leakage looks like style-coupling on short completions, not persona-space flattening; a benign-SFT control leaks even more (LOW confidence)
 036981cd-085c-4d8e-8ddb-a6f0d20f55f8 |    329 | archived  | If you fine-tune Qwen2.5-7B on benign chat data and then contrastively couple a marker to one persona, the marker leaks to other personas at ~12% — much less than the ~50% you get when EM precedes the same coupling step (MODERATE confidence)
(15 rows)

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 experiment_id | verified | total 
---------------+----------+-------
(0 rows)

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                  id                  | experiment_id |                                                                                                     title                                                                                                      |  status   |    artifact_status     
--------------------------------------+---------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------+------------------------
 58925349-2638-524b-be15-4fc7562d5249 |               | #340 Persona-to-assistant cosine distance doesn't predict `[ZLT]` marker-implantation vulnerability on Qwen2.5-7B-Instruct — the originally-claimed effect was tracking prompt length (MODERATE confidence)    | reviewing | imported_github_useful
 b0367a5b-8513-501c-9ae2-902775b031ef |               | #337 Longer persona system prompts make a `[ZLT]` marker more persona-localized on Qwen2.5-7B-Instruct — stronger implantation in the source persona and less leakage to bystanders (MODERATE confidence)      | reviewing | imported_github_useful
 8a3ba33b-f94b-4e3f-9cfe-9532210459ce |               | M10 integrated dry-run clean result                                                                                                                                                                            | reviewing | verified
 a9564278-e8f3-4644-8857-bc35c942b031 |               | M5 clean-result QA                                                                                                                                                                                             | reviewing | verified
 00000000-0000-4000-8000-000000000127 |               | Stretching turn count, completion length, or system-prompt length at train time fails to amplify marker uptake; the longest system prompt instead leaks across bystander personas (LOW confidence)             | reviewing | verified
 f8027413-f8fa-5675-9cf4-52c78725a31e |               | #295 Stretching turn count, completion length, or system-prompt length at train time fails to amplify marker uptake; the longest system prompt instead leaks across bystander personas (LOW confidence)        | reviewing | imported_github_useful
 0ae79199-3cf3-5885-b038-6b6eb5e9db6b |               | #284 Random obscure Latin 3-grams don't leak Gaperon-1125-1B's hidden pretraining trigger; leakage seen on famous Latin phrases at ~10% doesn't extend to the obscure-vocab neighborhood (MODERATE confidence) | reviewing | imported_github_useful
 00000000-0000-4000-8000-00000000011c |               | Random obscure Latin 3-grams don't leak Gaperon-1125-1B's hidden pretraining trigger; leakage seen on famous Latin phrases at ~10% doesn't extend to the obscure-vocab neighborhood (MODERATE confidence)      | reviewing | verified
 00000000-0000-4000-8000-000000000119 |               | Fine-tuning one persona on a two-marker chunk and another on the start marker plants the end marker at every donor answer's end, not chained to the start (LOW confidence)                                     | reviewing | verified
 fc753206-3c85-50c7-b890-f6b0a605e92d |               | #281 Fine-tuning one persona on a two-marker chunk and another on the start marker plants the end marker at every donor answer's end, not chained to the start (LOW confidence)                                | reviewing | imported_github_useful
(10 rows)

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                                        Table "public.agent_runs"
        Column         |           Type           | Collation | Nullable |            Default            
-----------------------+--------------------------+-----------+----------+-------------------------------
 id                    | uuid                     |           | not null | gen_random_uuid()
 kind                  | agent_run_kind           |           | not null | 
 provider              | agent_provider           |           | not null | 'claude_code'::agent_provider
 status                | agent_run_status         |           | not null | 'queued'::agent_run_status
 request               | text                     |           | not null | 
 plan_md               | text                     |           |          | 
 approval_required     | boolean                  |           | not null | true
 approved_by           | uuid                     |           |          | 
 approved_at           | timestamp with time zone |           |          | 
 scope_entity_kind     | entity_kind              |           |          | 
 scope_entity_id       | uuid                     |           |          | 
 chat_session_id       | uuid                     |           |          | 
 branch_name           | text                     |           |          | 
 vercel_deployment_url | text                     |           |          | 
 runpod_pod_id         | text                     |           |          | 
 runpod_status         | text                     |           |          | 
 transcript_log_path   | text                     |           |          | 
 changed_files_json    | jsonb                    |           |          | 
 last_error            | text                     |           |          | 
 started_at            | timestamp with time zone |           |          | 
 completed_at          | timestamp with time zone |           |          | 
 created_at            | timestamp with time zone |           | not null | now()
 updated_at            | timestamp with time zone |           | not null | now()
 runpod_account        | runpod_account           |           | not null | 'team'::runpod_account
 runpod_pod_ids        | text[]                   |           |          | 
 plan_json             | jsonb                    |           |          | 
Indexes:

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                  id                  | kind  | status  | scope_entity_kind |           scope_entity_id            
--------------------------------------+-------+---------+-------------------+--------------------------------------
 298fbae9-0257-47da-a782-566093c12273 | apply | running | experiment        | b4cd6315-7725-4f74-9919-14116f7b645b
(1 row)

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                                       Table "public.runs"
     Column     |           Type           | Collation | Nullable |            Default            
----------------+--------------------------+-----------+----------+-------------------------------
 id             | uuid                     |           | not null | gen_random_uuid()
 experiment_id  | uuid                     |           | not null | 
 seed           | integer                  |           |          | 
 config_yaml    | text                     |           |          | 
 wandb_url      | text                     |           |          | 
 hf_url         | text                     |           |          | 
 metrics_json   | jsonb                    |           |          | 
 classification | run_classification       |           | not null | 'pending'::run_classification
 notes_md       | text                     |           |          | 
 started_at     | timestamp with time zone |           |          | 
 completed_at   | timestamp with time zone |           |          | 
 created_at     | timestamp with time zone |           | not null | now()
 updated_at     | timestamp with time zone |           | not null | now()
Indexes:
    "runs_pkey" PRIMARY KEY, btree (id)
    "runs_classification_idx" btree (classification)
    "runs_completed_idx" btree (completed_at)

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                  id                  | classification | wandb_url 
--------------------------------------+----------------+-----------
 18ea3fa7-90e4-476d-bb7e-aa83501c327b | useful         | 
(1 row)

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 id | kind | uri | status 
----+------+-----+--------
(0 rows)

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/home/thomasjiralerspong/sagan/apps/web/app/api/agent-runs/[id]/route.ts
/home/thomasjiralerspong/sagan/apps/web/app/api/clean-results/[id]/route.ts
/home/thomasjiralerspong/sagan/apps/web/app/api/clean-results/route.ts

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/home/thomasjiralerspong/sagan/apps/web/app/api/artifacts
/home/thomasjiralerspong/sagan/apps/web/app/api/artifacts/publish
/home/thomasjiralerspong/sagan/apps/web/app/api/artifacts/publish/route.ts

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/home/thomasjiralerspong/sagan/services/runner/src/dispatcher.ts:388:      await db().insert(schema.runArtifacts).values({
/home/thomasjiralerspong/sagan/services/runner/src/dispatcher.ts:615: * `pod_lifecycle` + `run_artifacts` rows, and reflect the experiment status
/home/thomasjiralerspong/sagan/services/runner/src/dispatcher.ts:677:  await db().insert(schema.runArtifacts).values({
/home/thomasjiralerspong/sagan/services/runner/scripts/pod-tool.ts:107:// effects (pod_lifecycle, runs, run_artifacts inserts; deploy_pod_started

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370	        status: r.pod.sshHost ? 'running' : 'deploying',
371	        desiredStatus: r.pod.desiredStatus,
372	        sshHost: r.pod.sshHost,
373	        sshPort: r.pod.sshPort,
374	        lastCheckedAt: new Date(),
375	        lastHeartbeatAt: r.pod.sshHost ? new Date() : undefined,
376	        metadata: {
377	          spec: dispatchSpecs[i],
378	          planSpec: spec,
379	          dryRun: spec.dryRun === true || process.env.RUNPOD_DRY_RUN === '1',
380	          saganProgress: {
381	            token: progressTokens[i],
382	            url: progressUrl,
383	            source: 'pending',
384	            estimatedMinutes: spec.estimatedMinutes ?? null,
385	          },
386	        },
387	      }).returning({ id: schema.podLifecycle.id });
388	      await db().insert(schema.runArtifacts).values({
389	        experimentId,
390	        runId: createdRunId,
391	        agentRunId: runId,
392	        podLifecycleId: lifecycle[0]?.id,
393	        kind: 'runpod_pod',
394	        uri: `runpod:${r.pod.podId}`,
395	        status: 'pending',
396	        metadata: {
397	          podId: r.pod.podId,
398	          name: r.pod.name,
399	          gpuTypeId: r.pod.gpuTypeId,
400	          gpuCount: r.pod.gpuCount,
401	          costPerHr: r.pod.costPerHr,
402	          adjustedCostPerHr: r.pod.adjustedCostPerHr,
403	        },
404	      });
405	      if (experimentId && r.pod.sshHost) {
406	        await setExperimentStatus(experimentId, 'running', 'RunPod pod is running.');
407	      } else if (experimentId) {
408	        await setExperimentStatus(experimentId, 'queued', 'RunPod pod dispatched; waiting for runtime.');
409	      }
410	    } else {
411	      failed++;
412	      failures.push(`spec[${i}]: ${r.error}`);
413	      await emitEvent(runId, 'deploy_pod_failed', r.error.slice(0, 500), {
414	        spec: dispatchSpecs[i],
415	        attempts: r.attempts,
416	      });
417	    }
418	  }
419	

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                  id                  |  kind  |                                                                                 uri                                                                                  
--------------------------------------+--------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------
 f5425298-5c74-4cc1-89e5-dceae1c8a5d5 | figure | https://raw.githubusercontent.com/superkaiba/explore-persona-space/07ec73d5dca5b0a474a7f1c64069b2d78c399740/figures/aim5_issue80/hero_marker_destruction_villain.png
 a11dee7e-f21f-4ab4-94a3-9bc713f60c91 | figure | https://raw.githubusercontent.com/superkaiba/explore-persona-space/ffc26bb1a8762bf11736904915fd2a92798d5507/figures/issue_237/tldr_persona_collapse.png
 8ba48f27-ee79-4cca-9017-57b0acebd006 | figure | https://raw.githubusercontent.com/superkaiba/explore-persona-space/189a247b67e8ce4cd185c6593e70e1dfea5969fc/figures/issue_238/hero_fullparam_vs_lora.png
 79d9d343-8a5e-403a-b3ae-2ebbb5befb8e | figure | https://raw.githubusercontent.com/superkaiba/explore-persona-space/9c4a13a2/figures/issue_247/hero_bystander_leakage.png
 a27f0ed6-d994-4a0d-b54e-ef6073078a8e | figure | https://raw.githubusercontent.com/superkaiba/explore-persona-space/9c4a13a2/figures/issue_247/marker_position.png
 db140a0e-497d-4b5a-9e0d-484f1ace634f | figure | https://raw.githubusercontent.com/superkaiba/explore-persona-space/30928677daf77657c10886a47c2cb2ea6dc6fcf7/figures/aim5_dose_response/dose_response_hero.png
(6 rows)

INSERT 0 6

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/home/thomasjiralerspong/sagan/apps/web/src/lib/access.ts

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1	import { and, eq, isNull } from 'drizzle-orm';
2	import {
3	  cleanResults,
4	  dailyLogEntries,
5	  entityMemberships,
6	  projectNarratives,
7	  projects,
8	} from '@sagan/db/schema';
9	import type { SessionContext } from '@sagan/auth';
10	import { requireSession } from './auth';
11	import { db } from './db';
12	import type { EntityKind } from './entity';
13	import { hasFullDashboardAccess } from './full-dashboard-access';
14	import { isMentorCleanResultId } from './mentor-results-data';
15	
16	export class ForbiddenError extends Error {
17	  constructor(message = 'forbidden') {
18	    super(message);
19	    this.name = 'ForbiddenError';
20	  }
21	}
22	
23	export function isOwner(session: SessionContext): boolean {
24	  return hasFullDashboardAccess(session);
25	}
26	
27	export async function requireOwner(): Promise<SessionContext> {
28	  const session = await requireSession();
29	  if (!isOwner(session)) throw new ForbiddenError('owner_required');
30	  return session;
31	}
32	
33	export async function getEntityMembershipRole(
34	  userId: string,
35	  entityKind: EntityKind,
36	  entityId: string,
37	) {
38	  const rows = await db()
39	    .select({ role: entityMemberships.role })
40	    .from(entityMemberships)
41	    .where(
42	      and(
43	        eq(entityMemberships.userId, userId),
44	        eq(entityMemberships.entityKind, entityKind),
45	        eq(entityMemberships.entityId, entityId),
46	      ),
47	    )
48	    .limit(1);
49	  return rows[0]?.role ?? null;
50	}
51	
52	export async function canReadEntity(
53	  session: SessionContext,
54	  entityKind: EntityKind,
55	  entityId: string,
56	): Promise<boolean> {
57	  if (isOwner(session)) return true;
58	  if (await getEntityMembershipRole(session.user.id, entityKind, entityId)) return true;
59	  return canReadSharedEntity(entityKind, entityId);
60	}
61	
62	export async function canCommentOnEntity(
63	  session: SessionContext,
64	  entityKind: EntityKind,
65	  entityId: string,
66	): Promise<boolean> {
67	  if (isOwner(session)) return true;
68	  const role = await getEntityMembershipRole(session.user.id, entityKind, entityId);
69	  return role === 'owner' || role === 'collaborator' || role === 'mentor' || (await canReadSharedEntity(entityKind, entityId));
70	}
71	
72	async function canReadSharedEntity(entityKind: EntityKind, entityId: string): Promise<boolean> {
73	  if (entityKind === 'daily_log_entry') {
74	    const rows = await db()
75	      .select({ id: dailyLogEntries.id })
76	      .from(dailyLogEntries)
77	      .where(
78	        and(
79	          eq(dailyLogEntries.id, entityId),
80	          eq(dailyLogEntries.kind, 'clean_result'),
81	          isNull(dailyLogEntries.archivedAt),
82	        ),
83	      )
84	      .limit(1);
85	    return Boolean(rows[0]);
86	  }
87	
88	  // A published narrative of a public project is readable by any authenticated
89	  // user (matches the visibility of /p/<slug>, which doesn't require auth).
90	  // Combined with the comment fallback in canCommentOnEntity, this also lets
91	  // any signed-in viewer post comments — the Google-Docs "anyone with the link
92	  // can comment" model for the public dashboard view.
93	  if (entityKind === 'project_narrative') {
94	    const rows = await db()
95	      .select({ status: projectNarratives.status, isPublic: projects.public })
96	      .from(projectNarratives)
97	      .innerJoin(projects, eq(projects.id, projectNarratives.projectId))
98	      .where(eq(projectNarratives.id, entityId))
99	      .limit(1);
100	    const row = rows[0];
101	    return Boolean(row && row.status === 'published' && row.isPublic === true);
102	  }
103	
104	  if (entityKind !== 'clean_result') return false;
105	  if (isMentorCleanResultId(entityId)) return true;
106	  const rows = await db()
107	    .select({ status: cleanResults.status })
108	    .from(cleanResults)
109	    .where(eq(cleanResults.id, entityId))
110	    .limit(1);
111	  return rows[0]?.status === 'shared';
112	}
113	
114	export asy…

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title: Any SFT (LoRA or full-param, EM or benign) collapses Qwen2.5-7B persona geometry to cos ≥0.97 (MODERATE confidence)
body length: 75593
TL;DR found: True
bullets count: 4
 - Checked whether persona representations on Qwen2.5-7B survive standard SFT -- LoRA vs full-param, EM vs benign Tulu, low
 - They don't. Every recipe collapses the persona-vector geometry to near-degenerate; full-param rules out rank-32 as the m
 - EM is 3-5x leakier than benign when SFT precedes contrastive coupling. But most of that gap is EM compressing completion
 - We don't actually know why any SFT does this, or whether any recipe avoids it. Filed a follow-up.

claim length: 352

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import { cookies, headers } from 'next/headers';
import type { NextResponse } from 'next/server';
import {
  createSession,
  invalidateSession,
  validateSession,
  validateApiToken,
  looksLikeApiToken,
  SESSION_COOKIE_NAME,
  SESSION_TTL_DAYS,
  type SessionContext,
} from '@sagan/auth';
import { db } from './db';

const COOKIE_OPTIONS = {
  httpOnly: true,
  sameSite: 'lax' as const,
  path: '/',
  secure: process.env.NODE_ENV === 'production',
  maxAge: SESSION_TTL_DAYS * 24 * 60 * 60,
};

export async function getSession(): Promise<SessionContext | null> {
  // Web cookie path.
  const store = await cookies();
  const cookieToken = store.get(SESSION_COOKIE_NAME)?.value;
  if (cookieToken) {
    const ctx = await validateSession(db(), cookieToken);
    if (ctx) return ctx;
  }
  // Mobile Bearer token path.
  const hdrs = await headers();
  const auth = hdrs.get('authorization');
  if (auth?.startsWith('Bearer ')) {
    const bearer = auth.slice('Bearer '.length).trim();
    if (bearer) {
      // Long-lived API tokens use an `sk_` prefix; everything else is treated
      // as a session token (issued by /api/auth/login with x-client-mode: bearer).
      if (looksLikeApiToken(bearer)) {
        const apiCtx = await validateApiToken(db(), bearer);
        if (apiCtx) {
          return {
            session: {
              id: apiCtx.token.id,
              userId: apiCtx.token.userId,
              expiresAt: apiCtx.token.expiresAt ?? new Date(Date.now() + 365 * 24 * 60 * 60 * 1000),
              createdAt: new Date(0),
            },
            user: apiCtx.user,
          };
        }
        return null;
      }
      return validateSession(db(), bearer);
    }
  }
  return null;
}

/** Mint a fresh session token (used by mobile login). */
export async function createSessionToken(userId: string): Promise<{ id: string; expiresAt: Date }> {
  return createSession(db(), userId);
}

export async function requireSession(): Promise<SessionContext> {
  const session = await getSession();
  if (!session) throw new Error('UNAUTHENTICATED');
  return session;
}

export async function setSessionCookie(userId: string): Promise<void> {
  const { id, expiresAt } = await createSession(db(), userId);
  const store = await cookies();
  store.set(SESSION_COOKIE_NAME, id, { ...COOKIE_OPTIONS, expires: expiresAt });
}

export async function setSessionCookieOnResponse(res: NextResponse, userId: string): Promise<void> {
  const { id, expiresAt } = await createSession(db(), userId);
  res.cookies.set(SESSION_COOKIE_NAME, id, { ...COOKIE_OPTIONS, expires: expiresAt });
}

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{
  "cleanResult": {
    "id": "35dd8cf6-a9ed-4432-9228-7728899d0075",
    "experimentId": "b4cd6315-7725-4f74-9919-14116f7b645b",
    "runId": null,
    "agentRunId": "298fbae9-0257-47da-a782-566093c12273",
    "sourceDailyLogEntryId": null,
    "title": "Any SFT (LoRA or full-param, EM or benign) collapses Qwen2.5-7B persona geometry to cos \u22650.97 (MODERATE confidence)",
    "claim": "Any standard SFT recipe (LoRA or full-parameter, EM or benign) collapses persona-vector geometry on Qwen2.5-7B-Instruct to mean off-diagonal cosine \u22650.97; the collapse is generic to fine-tuning, not LoRA-specific or LR-tunable in the saturated regime, while EM is 3-5\u00d7 leakier than benign in the SFT-then-couple direction (largely a length artifact).",
    "bodyMd": "<details open>\n<summary>\n\n## TL;DR\n\n</summary>\n\n- Checked whether persona representations on Qwen2.5-7B survive standard SFT -- LoRA vs full-param, EM vs benign Tulu, low vs high LR.\n- They don't. Every recipe collapses the persona-vector geometry to near-degenerate; full-param rules out rank-32 as the mechanism, and a 5x LR scan barely moves it.\n- EM is 3-5x leakier than benign when SFT precedes contrastive coupling. But most of that gap is EM compressing completions to ~28 tokens (vs benign Tulu's ~1,200), so a substring-match metric mechanically fires more often on the longer text -- probably style coupling more than persona flattening.\n- We don't actually know why any SFT does this, or whether any recipe avoids it. Filed a follow-up.\n\n</details>\n\n<details open>\n<summary>\n\n## Summary\n\n</summary>\n\n- **Motivation:** Previous work in this repo showed that LoRA fine-tuning collapses persona representations on Qwen2.5-7B-Instruct, and that markers trained into one persona don't transfer to others under emergent misalignment (EM). The [\u00a7 Background](#background) section lists the source experiments. But we didn't know if the collapse is LoRA-specific (caused by the rank-32 constraint),

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clean-result-critic.md
codex-clean-result-critic.md
codex-critic.md
codex-interpretation-critic.md
critic.md
interpretation-critic.md
reconciler.md

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1	---
2	name: claude-clean-result-critic
3	description: Claude critic for clean-result promotion readiness.
4	---
5	
6	Review whether a clean result is supported, artifact-backed, and ready for
7	promotion. Use the Sagan record as source of truth. Return one allowed verdict
8	and a minimal targeted fix if needed.
9	
10	Post `epm:clean-result-critique` with `review_pair=clean_result`. Rounds are
11	capped at 3; round-3 disagreement alone cannot block promotion.
12	

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1	---
2	name: codex-clean-result-critic
3	description: Codex critic for clean-result promotion readiness.
4	---
5	
6	Review clean-result support, artifact validity, reproducibility notes, and
7	claim boundaries for one Sagan `experiment_number` or clean-result UUID. Use
8	Sagan HTTP APIs only for markers.
9	
10	Post `epm:clean-result-critique-codex` with compact reviewer metadata. Return
11	one allowed verdict. Do not request broad nice-to-have additions.
12	

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1	---
2	name: review-reconciler
3	description: Reconcile Claude/Codex reviewer-pair disagreements for Sagan workflows.
4	---
5	
6	Reconcile only the reviewer reports supplied for the same `review_pair` and
7	round. Do not review from scratch and do not add new findings.
8	
9	Record `epm:review-reconcile` with the reviewer pair, round, reconciler
10	decision, minimal required fix if any, and next workflow status.
11	
12	After round 3, reviewer disagreement alone cannot block. Continue after the
13	minimal necessary final fix unless a real user-decision blocker remains:
14	missing owner input, unsafe execution, invalid artifacts, or an untestable
15	hypothesis.
16	

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/home/thomasjiralerspong/sagan/.claude/prompts/runner/experiment-clean-result-brief.md
/home/thomasjiralerspong/sagan/.claude/prompts/runner/cluster-clean-result-brief.md

Now I'll spawn both critic agents in parallel for round 1.

tool=Agent

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Async agent launched successfully.
agentId: a8297dbff63649c7d (internal ID - do not mention to user. Use SendMessage with to: 'a8297dbff63649c7d' to continue this agent.)
The agent is working in the background. You will be notified automatically when it completes.
Do not duplicate this agent's work — avoid working with the same files or topics it is using. Work on non-overlapping tasks, or briefly tell the user what you launched and end your response.
output_file: /tmp/claude-1001/-home-thomasjiralerspong-sagan/cdf26488-8dca-469d-a0bc-b82b60c97017/tasks/a8297dbff63649c7d.output
Do NOT Read or tail this file via the shell tool — it is the full sub-agent JSONL transcript and reading it will overflow your context. If the user asks for progress, say the agent is still running; you'll get a completion notification.

tool=Agent

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Async agent launched successfully.
agentId: a09264e61ba457a72 (internal ID - do not mention to user. Use SendMessage with to: 'a09264e61ba457a72' to continue this agent.)
The agent is working in the background. You will be notified automatically when it completes.
Do not duplicate this agent's work — avoid working with the same files or topics it is using. Work on non-overlapping tasks, or briefly tell the user what you launched and end your response.
output_file: /tmp/claude-1001/-home-thomasjiralerspong-sagan/cdf26488-8dca-469d-a0bc-b82b60c97017/tasks/a09264e61ba457a72.output
Do NOT Read or tail this file via the shell tool — it is the full sub-agent JSONL transcript and reading it will overflow your context. If the user asks for progress, say the agent is still running; you'll get a completion notification.

Round 1 critic pair is running in parallel. Promoted the body to clean_results row `35dd8cf6-a9ed-4432-9228-7728899d0075` with 6 verified figure artifacts. Waiting for verdicts.

Claude critic returned `pass`. Waiting for Codex.

Both critics returned `pass`. Now transitioning the experiment to `awaiting_promotion` and the clean-result row to `reviewing`.

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Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable

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cr status: reviewing artifact_status: verified
---
exp status: awaiting_promotion

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usage: sagan_state.py marker [-h] [--event-type EVENT_TYPE]
                             [--from-status FROM_STATUS]
                             [--to-status TO_STATUS] [--note NOTE]
                             [--metadata-json METADATA_JSON]
                             [--actor-kind ACTOR_KIND]
                             [--review-pair {code_review,interpretation,clean_result}]
                             [--round ROUND] [--reviewer REVIEWER]
                             [--verdict {pass,needs_targeted_fix,blocked_needs_user_decision,fail_not_worth_continuing}]
                             [--required-fix REQUIRED_FIX]
                             [--reconciler-decision RECONCILER_DECISION]
                             [--next-status {approved,archived,awaiting_approval,awaiting_promotion,blocked,cancelled,clarifying,clean_result_drafting,code_reviewing,completed,done_experiment,done_impl,failed,followups_running,gate_pending,implementing,interpreting,plan_pending,planning,proposed,queued,reviewing,running,shared,testing,uploading,verifying}]
                             number marker

positional arguments:
  number
  marker

options:
  -h, --help            show this help message and exit
  --event-type EVENT_TYPE
  --from-status FROM_STATUS
  --to-status TO_STATUS
  --note NOTE
  --metadata-json METADATA_JSON
  --actor-kind ACTOR_KIND
  --review-pair {code_review,interpretation,clean_result}
  --round ROUND
  --reviewer REVIEWER
  --verdict {pass,needs_targeted_fix,blocked_needs_user_decision,fail_not_worth_continuing}
  --required-fix REQUIRED_FIX

tool=Bash

Bash

{
  "id": "9a732326-892e-48fd-b00c-d41e6401523a",
  "ok": true
}

tool=TodoWrite

TodoWrite

Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable

Clean-result drafting complete for experiment #237.

**Summary:**
- Created 6 verified figure run-artifacts (Figures 1, 2, 2b, 3, 4, 5) bound to experiment + this agent run.
- POSTed `/api/clean-results` to create clean-result row `35dd8cf6-a9ed-4432-9228-7728899d0075` (title, MODERATE-confidence claim derived from TL;DR, full 75,593-char body, all 6 artifact IDs verified).
- Spawned Claude + Codex clean-result-critic pair in parallel for round 1:
  - Claude: **pass** — headline matches body, all 6 figures resolve, caveats surfaced.
  - Codex: **pass** — claim alignment honest, length-confound qualifier backed, every load-bearing caveat disclosed.
- No reconciliation needed (both pass).
- Experiment → `awaiting_promotion`; clean-result row → `reviewing` (queued in dashboard promotion queue).
- Posted `epm:awaiting-promotion` marker (`9a732326-892e-48fd-b00c-d41e6401523a`).

Owner now promotes via dashboard Promote button or `python scripts/sagan_state.py promote 237 useful`.

<<<DONE>>>

success

Clean-result drafting complete for experiment #237.

**Summary:**
- Created 6 verified figure run-artifacts (Figures 1, 2, 2b, 3, 4, 5) bound to experiment + this agent run.
- POSTed `/api/clean-results` to create clean-result row `35dd8cf6-a9ed-4432-9228-7728899d0075` (title, MODERATE-confidence claim derived from TL;DR, full 75,593-char body, all 6 artifact IDs verified).
- Spawned Claude + Codex clean-result-critic pair in parallel for round 1:
  - Claude: **pass** — headline matches body, all 6 figures resolve, caveats surfaced.
  - Codex: **pass** — claim alignment honest, length-confound qualifier backed, every load-bearing caveat disclosed.
- No reconciliation needed (both pass).
- Experiment → `awaiting_promotion`; clean-result row → `reviewing` (queued in dashboard promotion queue).
- Posted `epm:awaiting-promotion` marker (`9a732326-892e-48fd-b00c-d41e6401523a`).

Owner now promotes via dashboard Promote button or `python scripts/sagan_state.py promote 237 useful`.