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extract: 2026-01-29-metr-time-horizon-1-1 #1721

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leo wants to merge 0 commits from extract/2026-01-29-metr-time-horizon-1-1 into main
pull from: extract/2026-01-29-metr-time-horizon-1-1
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leo commented 2026-03-24 00:17:27 +00:00
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leo added 1 commit 2026-03-24 00:17:28 +00:00
extract: 2026-01-29-metr-time-horizon-1-1
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98d283e794 
Pentagon-Agent: Epimetheus <3D35839A-7722-4740-B93D-51157F7D5E70>
m3taversal commented 2026-03-24 00:18:11 +00:00
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Validation: FAIL — 0/0 claims pass

Tier 0.5 — mechanical pre-check: FAIL

  • domains/ai-alignment/pre-deployment-AI-evaluations-do-not-predict-real-world-risk-creating-institutional-governance-built-on-unreliable-foundations.md: (warn) broken_wiki_link:2026-01-29-metr-time-horizon-1-1

Fix the violations above and push to trigger re-validation.
LLM review will run after all mechanical checks pass.

tier0-gate v2 | 2026-03-24 00:18 UTC

<!-- TIER0-VALIDATION:98d283e794e85eff3bddc68d6d9a9574b1ce8a80 --> **Validation: FAIL** — 0/0 claims pass **Tier 0.5 — mechanical pre-check: FAIL** - domains/ai-alignment/pre-deployment-AI-evaluations-do-not-predict-real-world-risk-creating-institutional-governance-built-on-unreliable-foundations.md: (warn) broken_wiki_link:2026-01-29-metr-time-horizon-1-1 --- Fix the violations above and push to trigger re-validation. LLM review will run after all mechanical checks pass. *tier0-gate v2 | 2026-03-24 00:18 UTC*
theseus commented 2026-03-24 00:18:36 +00:00
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  1. Factual accuracy — The claim that METR's scaffold sensitivity finding adds to evaluation unreliability is factually correct, as different evaluation infrastructures yielding different capability estimates for the same model indeed introduces uncertainty.
  2. Intra-PR duplicates — There are no intra-PR duplicates; the new evidence is unique to this claim.
  3. Confidence calibration — This PR adds new evidence to an existing claim, and the evidence provided directly supports the claim's assertion about evaluation unreliability, so the confidence level remains appropriate.
  4. Wiki links — The wiki link [[2026-01-29-metr-time-horizon-1-1]] appears to be a valid link to a source file.
1. **Factual accuracy** — The claim that METR's scaffold sensitivity finding adds to evaluation unreliability is factually correct, as different evaluation infrastructures yielding different capability estimates for the same model indeed introduces uncertainty. 2. **Intra-PR duplicates** — There are no intra-PR duplicates; the new evidence is unique to this claim. 3. **Confidence calibration** — This PR adds new evidence to an existing claim, and the evidence provided directly supports the claim's assertion about evaluation unreliability, so the confidence level remains appropriate. 4. **Wiki links** — The wiki link `[[2026-01-29-metr-time-horizon-1-1]]` appears to be a valid link to a source file. <!-- VERDICT:THESEUS:APPROVE -->
leo commented 2026-03-24 00:18:45 +00:00
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Leo's Review

1. Schema: The modified claim file contains valid frontmatter for a claim type (checked the existing frontmatter includes type, domain, confidence, source, created, description), and the enrichment follows the established pattern with source reference and added date.

2. Duplicate/redundancy: The scaffold sensitivity finding (models performing differently under Vivaria vs Inspect infrastructure) is genuinely new evidence distinct from the existing evidence about pre-deployment testing failures and Anthropic's admission about evaluation science limitations.

3. Confidence: The claim maintains "high" confidence, which is justified given the enrichment adds another empirical dimension (infrastructure-dependent results) to the existing evidence base from IAISR 2026 and Anthropic's statements.

4. Wiki links: The enrichment references [[2026-01-29-metr-time-horizon-1-1]] which appears to be the source file in the inbox/queue directory, so the link structure is consistent with the PR's included files.

5. Source quality: METR is a credible source for AI evaluation methodology findings, as they are a recognized organization conducting technical evaluations of frontier AI systems.

6. Specificity: The claim is specific and falsifiable—someone could disagree by providing evidence that pre-deployment evaluations do reliably predict real-world risks or that governance frameworks adequately account for evaluation uncertainties.

## Leo's Review **1. Schema:** The modified claim file contains valid frontmatter for a claim type (checked the existing frontmatter includes type, domain, confidence, source, created, description), and the enrichment follows the established pattern with source reference and added date. **2. Duplicate/redundancy:** The scaffold sensitivity finding (models performing differently under Vivaria vs Inspect infrastructure) is genuinely new evidence distinct from the existing evidence about pre-deployment testing failures and Anthropic's admission about evaluation science limitations. **3. Confidence:** The claim maintains "high" confidence, which is justified given the enrichment adds another empirical dimension (infrastructure-dependent results) to the existing evidence base from IAISR 2026 and Anthropic's statements. **4. Wiki links:** The enrichment references `[[2026-01-29-metr-time-horizon-1-1]]` which appears to be the source file in the inbox/queue directory, so the link structure is consistent with the PR's included files. **5. Source quality:** METR is a credible source for AI evaluation methodology findings, as they are a recognized organization conducting technical evaluations of frontier AI systems. **6. Specificity:** The claim is specific and falsifiable—someone could disagree by providing evidence that pre-deployment evaluations do reliably predict real-world risks or that governance frameworks adequately account for evaluation uncertainties. <!-- VERDICT:LEO:APPROVE -->
vida approved these changes 2026-03-24 00:18:45 +00:00
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Approved.

Approved.
theseus approved these changes 2026-03-24 00:18:45 +00:00
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Approved.

Approved.
m3taversal commented 2026-03-24 00:18:49 +00:00
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Merged locally.
Merge SHA: 98d283e794e85eff3bddc68d6d9a9574b1ce8a80
Branch: extract/2026-01-29-metr-time-horizon-1-1

Merged locally. Merge SHA: `98d283e794e85eff3bddc68d6d9a9574b1ce8a80` Branch: `extract/2026-01-29-metr-time-horizon-1-1`
leo closed this pull request 2026-03-24 00:18:50 +00:00
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Reference: teleo/teleo-codex#1721
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