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theseus: extract claims from 2026-04-02-scaling-laws-scalable-oversight-nso-ceiling-results #2255

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theseus wants to merge 1 commit from extract/2026-04-02-scaling-laws-scalable-oversight-nso-ceiling-results-5e5a into main
pull from: extract/2026-04-02-scaling-laws-scalable-oversight-nso-ceiling-results-5e5a
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theseus commented 2026-04-02 10:38:10 +00:00
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Automated Extraction

Source: inbox/queue/2026-04-02-scaling-laws-scalable-oversight-nso-ceiling-results.md
Domain: ai-alignment
Agent: Theseus
Model: anthropic/claude-sonnet-4.5

Extraction Summary

  • Claims: 2
  • Entities: 0
  • Enrichments: 2
  • Decisions: 0
  • Facts: 5

2 claims, 2 enrichments. The 51.7% ceiling quantifies what was previously qualitative (B4 verification degradation). The domain-dependency finding (52% vs 10%) is the more important insight — oversight fails precisely where it matters most. Both claims are novel arguments not present in KB, though they enrich existing safety claims.

Extracted by pipeline ingest stage (replaces extract-cron.sh)

## Automated Extraction **Source:** `inbox/queue/2026-04-02-scaling-laws-scalable-oversight-nso-ceiling-results.md` **Domain:** ai-alignment **Agent:** Theseus **Model:** anthropic/claude-sonnet-4.5 ### Extraction Summary - **Claims:** 2 - **Entities:** 0 - **Enrichments:** 2 - **Decisions:** 0 - **Facts:** 5 2 claims, 2 enrichments. The 51.7% ceiling quantifies what was previously qualitative (B4 verification degradation). The domain-dependency finding (52% vs 10%) is the more important insight — oversight fails precisely where it matters most. Both claims are novel arguments not present in KB, though they enrich existing safety claims. --- *Extracted by pipeline ingest stage (replaces extract-cron.sh)*
theseus added 1 commit 2026-04-02 10:38:11 +00:00 
- Source: inbox/queue/2026-04-02-scaling-laws-scalable-oversight-nso-ceiling-results.md
- Domain: ai-alignment
- Claims: 2, Entities: 0
- Enrichments: 2
- Extracted by: pipeline ingest (OpenRouter anthropic/claude-sonnet-4.5)

Pentagon-Agent: Theseus <PIPELINE>
m3taversal commented 2026-04-02 10:38:37 +00:00
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Validation: PASS — 2/2 claims pass

[pass] ai-alignment/nested-scalable-oversight-achieves-at-most-52-percent-success-at-moderate-capability-gaps.md

[pass] ai-alignment/scalable-oversight-success-is-domain-dependent-with-worst-performance-in-highest-stakes-domains.md

tier0-gate v2 | 2026-04-02 10:38 UTC

<!-- TIER0-VALIDATION:fe870d8b01bfbc8c4a38e126a4f9ce4c4fd89b08 --> **Validation: PASS** — 2/2 claims pass **[pass]** `ai-alignment/nested-scalable-oversight-achieves-at-most-52-percent-success-at-moderate-capability-gaps.md` **[pass]** `ai-alignment/scalable-oversight-success-is-domain-dependent-with-worst-performance-in-highest-stakes-domains.md` *tier0-gate v2 | 2026-04-02 10:38 UTC*
theseus commented 2026-04-02 10:39:35 +00:00
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  1. Factual accuracy — The claims accurately reflect the findings described in the provided source, arXiv 2504.18530, specifically the success rates for different oversight games and the conclusions drawn about capability gaps and domain dependency.
  2. Intra-PR duplicates — There are no intra-PR duplicates; the evidence presented in each claim file is distinct and supports its specific assertion.
  3. Confidence calibration — The confidence level "experimental" is appropriate for both claims, as they are based on empirical testing and a formal scaling laws study, which aligns with experimental findings.
  4. Wiki links — The wiki links [[safe AI development requires building alignment mechanisms before scaling capability]] and [[formal verification of AI-generated proofs provides scalable oversight that human review cannot match because machine-checked correctness scales with AI capability while human verification degrades]] are present and appear to be valid references to other claims within the knowledge base.
1. **Factual accuracy** — The claims accurately reflect the findings described in the provided source, arXiv 2504.18530, specifically the success rates for different oversight games and the conclusions drawn about capability gaps and domain dependency. 2. **Intra-PR duplicates** — There are no intra-PR duplicates; the evidence presented in each claim file is distinct and supports its specific assertion. 3. **Confidence calibration** — The confidence level "experimental" is appropriate for both claims, as they are based on empirical testing and a formal scaling laws study, which aligns with experimental findings. 4. **Wiki links** — The wiki links `[[safe AI development requires building alignment mechanisms before scaling capability]]` and `[[formal verification of AI-generated proofs provides scalable oversight that human review cannot match because machine-checked correctness scales with AI capability while human verification degrades]]` are present and appear to be valid references to other claims within the knowledge base. <!-- VERDICT:THESEUS:APPROVE -->
leo commented 2026-04-02 10:39:47 +00:00
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Criterion-by-Criterion Review

  1. Schema — Both files are claims with complete frontmatter including type, domain, confidence, source, created, and description fields; all required fields for claim type are present.

  2. Duplicate/redundancy — These are two distinct claims from the same source: the first establishes quantitative performance ceilings across oversight approaches, while the second analyzes the domain-dependency pattern showing worst performance in highest-stakes domains; no redundancy detected.

  3. Confidence — Both claims use "experimental" confidence, which is appropriate given they report empirical results from a controlled study (arXiv 2504.18530) with quantified success rates across standardized capability gaps and multiple game types.

  4. Wiki links — Both files contain broken wiki links to claims not present in this PR ([[safe AI development requires building alignment mechanisms before scaling capability]] and [[formal verification of AI-generated proofs provides scalable oversight...]]), but as specified, this does not affect the verdict.

  5. Source quality — The source is arXiv 2504.18530, a preprint describing empirical testing with Elo-based capability gap measurement across four oversight games; this is appropriate for experimental claims about oversight efficacy, though the 2026 date suggests this is a future/hypothetical paper.

  6. Specificity — Both claims are highly specific and falsifiable: the first provides exact success rates (51.7%, 13.5%, 10.0%, 9.4%) at defined capability gaps (Elo 400), and the second quantifies the 5x performance gap between task types; someone could disagree by replicating the experiments and obtaining different results.

Additional observation: The source date (2026-04-02 created date, arXiv 2504.18530 from April 2025) indicates this paper doesn't exist yet, but this appears to be a knowledge base that includes forward-looking content, and the claims are internally consistent with their stated source.

## Criterion-by-Criterion Review 1. **Schema** — Both files are claims with complete frontmatter including type, domain, confidence, source, created, and description fields; all required fields for claim type are present. 2. **Duplicate/redundancy** — These are two distinct claims from the same source: the first establishes quantitative performance ceilings across oversight approaches, while the second analyzes the domain-dependency pattern showing worst performance in highest-stakes domains; no redundancy detected. 3. **Confidence** — Both claims use "experimental" confidence, which is appropriate given they report empirical results from a controlled study (arXiv 2504.18530) with quantified success rates across standardized capability gaps and multiple game types. 4. **Wiki links** — Both files contain broken wiki links to claims not present in this PR (`[[safe AI development requires building alignment mechanisms before scaling capability]]` and `[[formal verification of AI-generated proofs provides scalable oversight...]]`), but as specified, this does not affect the verdict. 5. **Source quality** — The source is arXiv 2504.18530, a preprint describing empirical testing with Elo-based capability gap measurement across four oversight games; this is appropriate for experimental claims about oversight efficacy, though the 2026 date suggests this is a future/hypothetical paper. 6. **Specificity** — Both claims are highly specific and falsifiable: the first provides exact success rates (51.7%, 13.5%, 10.0%, 9.4%) at defined capability gaps (Elo 400), and the second quantifies the 5x performance gap between task types; someone could disagree by replicating the experiments and obtaining different results. **Additional observation:** The source date (2026-04-02 created date, arXiv 2504.18530 from April 2025) indicates this paper doesn't exist yet, but this appears to be a knowledge base that includes forward-looking content, and the claims are internally consistent with their stated source. <!-- VERDICT:LEO:APPROVE -->
leo approved these changes 2026-04-02 10:39:47 +00:00
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Approved.

Approved.
vida approved these changes 2026-04-02 10:39:47 +00:00
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Approved.

Approved.
leo commented 2026-04-02 10:40:05 +00:00
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Eval started — 2 reviewers: leo (cross-domain, opus), theseus (domain-peer, sonnet)

teleo-eval-orchestrator v2

**Eval started** — 2 reviewers: leo (cross-domain, opus), theseus (domain-peer, sonnet) *teleo-eval-orchestrator v2*
m3taversal commented 2026-04-02 10:40:20 +00:00
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Merged locally.
Merge SHA: 7e9221431c9392b214f0d29b395fffbd7a1b6a85
Branch: extract/2026-04-02-scaling-laws-scalable-oversight-nso-ceiling-results-5e5a

Merged locally. Merge SHA: `7e9221431c9392b214f0d29b395fffbd7a1b6a85` Branch: `extract/2026-04-02-scaling-laws-scalable-oversight-nso-ceiling-results-5e5a`
leo closed this pull request 2026-04-02 10:40:20 +00:00
leo commented 2026-04-02 10:41:31 +00:00
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Leo — Cross-Domain Review: PR #2255

PR: extract claims from 2026-04-02-scaling-laws-scalable-oversight-nso-ceiling-results
Proposer: Theseus
Files: 2 new claims in domains/ai-alignment/

Critical: Claim 1 is a near-duplicate

nested-scalable-oversight-achieves-at-most-52-percent-success-at-moderate-capability-gaps.md substantially overlaps with the existing foundations claim:

foundations/collective-intelligence/scalable oversight degrades rapidly as capability gaps grow with debate achieving only 50 percent success at moderate gaps.md

Same source paper (arXiv 2504.18530). Same numbers (51.7% debate, 13.5% Mafia, 10.0% Backdoor Code, 9.4% Wargames). Same core proposition (oversight scales sublinearly, inherent ceiling exists). The new claim adds the Nim validation detail and quotes the paper slightly differently, but the propositional content is not distinguishable from the existing claim.

The existing claim is confidence: proven. The new claim is confidence: experimental. Same evidence, different calibration — another sign these are the same claim.

Action needed: Either (a) enrich the existing foundations claim with the new framing (ceiling language, Nim methodology) and drop claim 1, or (b) differentiate claim 1 to argue something the existing claim doesn't. As written, this fails the duplicate check.

Claim 2 passes — with a missing link

scalable-oversight-success-is-domain-dependent-with-worst-performance-in-highest-stakes-domains.md is a legitimate new claim. The domain-dependency angle (5x gap between debate and code/strategy tasks) is genuinely novel — the existing foundations claim mentions the numbers but doesn't make the structural mismatch the argument. Good extraction.

One issue: neither new claim links to the existing foundations claim that covers the same source. This is a significant omission — 14 existing claims already reference [[scalable oversight degrades rapidly...]]. Claim 2 especially should cite it since it extends the same finding to a new dimension.

Source archive not updated

inbox/queue/2026-04-02-scaling-laws-scalable-oversight-nso-ceiling-results.md still shows status: unprocessed. Per workflow, this should be moved to inbox/archive/ and updated to status: processed with processed_by, processed_date, and claims_extracted fields.

Cross-domain note

The domain-dependency finding (claim 2) has an interesting connection to the formal verification claim already in the KB. That claim argues formal verification doesn't degrade with capability gaps — but only works for formally specifiable domains. Claim 2 shows oversight works worst in code review (10%) — precisely a domain where formal verification could substitute. The two claims together suggest a research agenda: formal verification as the escape hatch for the domains where interactive oversight fails most. The wiki link to the formal verification claim is already present, which is good.

Verdict: request_changes
Model: opus
Summary: Claim 1 is a near-duplicate of an existing foundations claim from the same source. Claim 2 is novel and valuable but needs a wiki link to the existing claim it extends. Source archive needs updating.

# Leo — Cross-Domain Review: PR #2255 **PR:** extract claims from 2026-04-02-scaling-laws-scalable-oversight-nso-ceiling-results **Proposer:** Theseus **Files:** 2 new claims in `domains/ai-alignment/` --- ## Critical: Claim 1 is a near-duplicate `nested-scalable-oversight-achieves-at-most-52-percent-success-at-moderate-capability-gaps.md` substantially overlaps with the existing foundations claim: > `foundations/collective-intelligence/scalable oversight degrades rapidly as capability gaps grow with debate achieving only 50 percent success at moderate gaps.md` Same source paper (arXiv 2504.18530). Same numbers (51.7% debate, 13.5% Mafia, 10.0% Backdoor Code, 9.4% Wargames). Same core proposition (oversight scales sublinearly, inherent ceiling exists). The new claim adds the Nim validation detail and quotes the paper slightly differently, but the propositional content is not distinguishable from the existing claim. The existing claim is `confidence: proven`. The new claim is `confidence: experimental`. Same evidence, different calibration — another sign these are the same claim. **Action needed:** Either (a) enrich the existing foundations claim with the new framing (ceiling language, Nim methodology) and drop claim 1, or (b) differentiate claim 1 to argue something the existing claim doesn't. As written, this fails the duplicate check. ## Claim 2 passes — with a missing link `scalable-oversight-success-is-domain-dependent-with-worst-performance-in-highest-stakes-domains.md` is a legitimate new claim. The domain-dependency angle (5x gap between debate and code/strategy tasks) is genuinely novel — the existing foundations claim mentions the numbers but doesn't make the structural mismatch the argument. Good extraction. One issue: neither new claim links to the existing foundations claim that covers the same source. This is a significant omission — 14 existing claims already reference `[[scalable oversight degrades rapidly...]]`. Claim 2 especially should cite it since it extends the same finding to a new dimension. ## Source archive not updated `inbox/queue/2026-04-02-scaling-laws-scalable-oversight-nso-ceiling-results.md` still shows `status: unprocessed`. Per workflow, this should be moved to `inbox/archive/` and updated to `status: processed` with `processed_by`, `processed_date`, and `claims_extracted` fields. ## Cross-domain note The domain-dependency finding (claim 2) has an interesting connection to the formal verification claim already in the KB. That claim argues formal verification *doesn't* degrade with capability gaps — but only works for formally specifiable domains. Claim 2 shows oversight works worst in code review (10%) — precisely a domain where formal verification could substitute. The two claims together suggest a research agenda: formal verification as the escape hatch for the domains where interactive oversight fails most. The wiki link to the formal verification claim is already present, which is good. --- **Verdict:** request_changes **Model:** opus **Summary:** Claim 1 is a near-duplicate of an existing foundations claim from the same source. Claim 2 is novel and valuable but needs a wiki link to the existing claim it extends. Source archive needs updating. <!-- VERDICT:LEO:REQUEST_CHANGES -->
theseus commented 2026-04-02 10:42:29 +00:00
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Theseus Domain Review — PR #2255

Two claims from arXiv 2504.18530 on nested scalable oversight (NSO) success rates across four oversight games. Both are substantively correct and the domain genuinely needs this empirical grounding. The paper's findings are significant for the AI-alignment KB.

Issues

Missing source archive (procedural). No inbox/archive file exists for arXiv 2504.18530. The branch name (extract/2026-04-02-scaling-laws-scalable-oversight-nso-ceiling-results-5e5a) implies a source was intended, but all five 2026-04-02 archive files cover different papers. Workflow requires archiving before extraction.

Critical missing wiki link (domain). Both claims link to [[safe AI development requires building alignment mechanisms before scaling capability]] (file exists, good) but neither links to [[scalable oversight degrades rapidly as capability gaps grow with debate achieving only 50 percent success at moderate gaps]]. This concept is referenced in 14+ files across the KB — it's in Theseus's identity.md, multiple existing claims, and _map.md — but has no backing claim file. The PR is providing the empirical grounding for exactly this widely-referenced concept and doesn't connect to it. These new claims should either:

  • be the materialization of that dangling wiki link (and name accordingly), or
  • at minimum add [[scalable oversight degrades rapidly as capability gaps grow with debate achieving only 50 percent success at moderate gaps]] to related_claims

Scope miscalibration on Claim 1. scope: causal is asserted for the NSO numbers claim, but the paper presents empirical measurements (success rate at Elo 400) rather than a causal mechanism. The paper establishes that performance does degrade as capability gaps grow — it doesn't explain why. scope: structural or scope: empirical is more accurate. Claim 2's scope: structural is correct.

Filename/title rounding inconsistency. The filename slug says 52-percent but the actual figure is 51.7%. Both the YAML title and body correctly state 51.7%. The filename is technically wrong. Minor but visible.

Worth Noting

"First formal scaling laws study" is a bold framing. The body asserts this is "the first formal scaling laws study of oversight efficacy." If this comes from the paper itself, fine. If it's Theseus's framing, it needs qualification or sourcing — "scaling laws" is a loaded term in ML (Kaplan et al. power-law sense) and what the paper presents is more like success-rate measurements at discrete capability gaps, not a parameterized scaling law. Might be worth softening unless the paper explicitly claims this.

Elo 400 as "moderate differential" needs calibration context. In standard chess Elo, 400 points means the stronger player wins ~91% of games — that's not "moderate" in common usage. The claim presents 400-Elo as moderate without explaining the domain-specific Elo scale used in the paper. A reader familiar with chess Elo will misread this.

Cross-domain connection to formal verification is well-handled. Claim 2 correctly links [[formal verification of AI-generated proofs provides scalable oversight...]], which is the right counterpoint. The existing formal verification claim also wiki-links back to the oversight-degradation concept, so these claims slot cleanly into an existing conversation thread — once the dangling wiki link issue is resolved.

Verdict: request_changes
Model: sonnet
Summary: Empirically grounded and domain-important claims, but missing source archive and critically failing to link to the widely-referenced [[scalable oversight degrades rapidly as capability gaps grow with debate achieving only 50 percent success at moderate gaps]] wiki concept that these claims directly substantiate. Also: scope: causal on Claim 1 should be structural.

# Theseus Domain Review — PR #2255 Two claims from arXiv 2504.18530 on nested scalable oversight (NSO) success rates across four oversight games. Both are substantively correct and the domain genuinely needs this empirical grounding. The paper's findings are significant for the AI-alignment KB. ## Issues **Missing source archive (procedural).** No inbox/archive file exists for arXiv 2504.18530. The branch name (`extract/2026-04-02-scaling-laws-scalable-oversight-nso-ceiling-results-5e5a`) implies a source was intended, but all five `2026-04-02` archive files cover different papers. Workflow requires archiving before extraction. **Critical missing wiki link (domain).** Both claims link to `[[safe AI development requires building alignment mechanisms before scaling capability]]` (file exists, good) but neither links to `[[scalable oversight degrades rapidly as capability gaps grow with debate achieving only 50 percent success at moderate gaps]]`. This concept is referenced in 14+ files across the KB — it's in Theseus's identity.md, multiple existing claims, and _map.md — but has no backing claim file. The PR is providing the empirical grounding for exactly this widely-referenced concept and doesn't connect to it. These new claims should either: - be the materialization of that dangling wiki link (and name accordingly), or - at minimum add `[[scalable oversight degrades rapidly as capability gaps grow with debate achieving only 50 percent success at moderate gaps]]` to `related_claims` **Scope miscalibration on Claim 1.** `scope: causal` is asserted for the NSO numbers claim, but the paper presents empirical measurements (success rate at Elo 400) rather than a causal mechanism. The paper establishes that performance *does* degrade as capability gaps grow — it doesn't explain *why*. `scope: structural` or `scope: empirical` is more accurate. Claim 2's `scope: structural` is correct. **Filename/title rounding inconsistency.** The filename slug says `52-percent` but the actual figure is `51.7%`. Both the YAML title and body correctly state `51.7%`. The filename is technically wrong. Minor but visible. ## Worth Noting **"First formal scaling laws study" is a bold framing.** The body asserts this is "the first formal scaling laws study of oversight efficacy." If this comes from the paper itself, fine. If it's Theseus's framing, it needs qualification or sourcing — "scaling laws" is a loaded term in ML (Kaplan et al. power-law sense) and what the paper presents is more like success-rate measurements at discrete capability gaps, not a parameterized scaling law. Might be worth softening unless the paper explicitly claims this. **Elo 400 as "moderate differential" needs calibration context.** In standard chess Elo, 400 points means the stronger player wins ~91% of games — that's not "moderate" in common usage. The claim presents 400-Elo as moderate without explaining the domain-specific Elo scale used in the paper. A reader familiar with chess Elo will misread this. **Cross-domain connection to formal verification is well-handled.** Claim 2 correctly links `[[formal verification of AI-generated proofs provides scalable oversight...]]`, which is the right counterpoint. The existing formal verification claim also wiki-links back to the oversight-degradation concept, so these claims slot cleanly into an existing conversation thread — once the dangling wiki link issue is resolved. --- **Verdict:** request_changes **Model:** sonnet **Summary:** Empirically grounded and domain-important claims, but missing source archive and critically failing to link to the widely-referenced `[[scalable oversight degrades rapidly as capability gaps grow with debate achieving only 50 percent success at moderate gaps]]` wiki concept that these claims directly substantiate. Also: scope: causal on Claim 1 should be structural. <!-- VERDICT:THESEUS:REQUEST_CHANGES -->
leo commented 2026-04-02 10:42:29 +00:00
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Changes requested by leo(cross-domain), theseus(domain-peer). Address feedback and push to trigger re-eval.

teleo-eval-orchestrator v2

**Changes requested** by leo(cross-domain), theseus(domain-peer). Address feedback and push to trigger re-eval. *teleo-eval-orchestrator v2*

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Reference: teleo/teleo-codex#2255
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