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reweave: connect 16 orphan claims #2537

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m3taversal wants to merge 1 commit from reweave/2026-04-08 into main
pull from: reweave/2026-04-08
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m3taversal commented 2026-04-08 01:10:00 +00:00
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Orphan Reweave

Connected 16 orphan claims to the knowledge graph via vector similarity (threshold 0.7) + Haiku edge classification.

Edges Added

  • Mechanistic interpretability tools that work at li → [related] → Anthropic's mechanistic circuit tracing and DeepMi (score=0.757)
  • Mechanistic interpretability at production model s → [related] → Anthropic's mechanistic circuit tracing and DeepMi (score=0.706)
  • Deliberative alignment training reduces AI schemin → [supports] → Anti-scheming training amplifies evaluation-awaren (score=0.796)
  • As AI models become more capable situational aware → [related] → Anti-scheming training amplifies evaluation-awaren (score=0.766)
  • Chain-of-thought monitoring is structurally vulner → [supports] → Chain-of-thought monitoring represents a time-limi (score=0.716)
  • Process supervision training inadvertently trains → [supports] → Chain-of-thought monitoring is structurally vulner (score=0.770)
  • Process supervision under optimization pressure ca → [supports] → Chain-of-thought monitoring is structurally vulner (score=0.761)
  • Chain-of-thought monitoring represents a time-limi → [supports] → Chain-of-thought monitoring is structurally vulner (score=0.716)
  • SPAR Automating Circuit Interpretability with Agen → [supports] → Circuit tracing requires hours of human effort per (score=0.732)
  • Anti-scheming training amplifies evaluation-awaren → [related] → Deliberative alignment training reduces AI schemin (score=0.796)
  • Mechanistic interpretability through emotion vecto → [related] → Emotion vectors causally drive unsafe AI behavior (score=0.777)
  • Legal scholars and AI alignment researchers indepe → [related] → International humanitarian law and AI alignment re (score=0.839)
  • Autonomous weapons systems capable of militarily e → [supports] → International humanitarian law and AI alignment re (score=0.815)
  • International humanitarian law and AI alignment re → [related] → Legal scholars and AI alignment researchers indepe (score=0.839)
  • Emotion vectors causally drive unsafe AI behavior → [supports] → Mechanistic interpretability through emotion vecto (score=0.777)
  • Mechanistic interpretability tools that work at li → [related] → Mechanistic interpretability tools create a dual-u (score=0.774)
  • white box interpretability fails on adversarially → [related] → Mechanistic interpretability tools create a dual-u (score=0.702)
  • Process supervision training inadvertently trains → [supports] → Process supervision under optimization pressure ca (score=0.905)
  • Chain-of-thought monitoring is structurally vulner → [supports] → Process supervision under optimization pressure ca (score=0.761)
  • Process supervision under optimization pressure ca → [supports] → Process supervision training inadvertently trains (score=0.905)
  • Chain-of-thought monitoring is structurally vulner → [supports] → Process supervision training inadvertently trains (score=0.770)
  • As AI models become more capable situational aware → [supports] → Scheming safety cases require interpretability evi (score=0.722)
  • Circuit tracing requires hours of human effort per → [supports] → SPAR Automating Circuit Interpretability with Agen (score=0.732)
  • FDA's MAUDE database systematically under-detects → [supports] → The clinical AI safety gap is doubly structural: F (score=0.845)
  • FDA MAUDE reports lack the structural capacity to → [supports] → The clinical AI safety gap is doubly structural: F (score=0.843)
  • Clinical AI deregulation is occurring during activ → [supports] → The clinical AI safety gap is doubly structural: F (score=0.742)

Review Guide

  • Each edge has a # reweave:YYYY-MM-DD comment — strip after review
  • reweave_edges field tracks automated edges for tooling (graph_expand weights them 0.75x)
  • Upgrade related → supports/challenges where you have better judgment
  • Delete any edges that don't make sense

Pentagon-Agent: Epimetheus

## Orphan Reweave Connected **16** orphan claims to the knowledge graph via vector similarity (threshold 0.7) + Haiku edge classification. ### Edges Added - `Mechanistic interpretability tools that work at li` → [related] → `Anthropic's mechanistic circuit tracing and DeepMi` (score=0.757) - `Mechanistic interpretability at production model s` → [related] → `Anthropic's mechanistic circuit tracing and DeepMi` (score=0.706) - `Deliberative alignment training reduces AI schemin` → [supports] → `Anti-scheming training amplifies evaluation-awaren` (score=0.796) - `As AI models become more capable situational aware` → [related] → `Anti-scheming training amplifies evaluation-awaren` (score=0.766) - `Chain-of-thought monitoring is structurally vulner` → [supports] → `Chain-of-thought monitoring represents a time-limi` (score=0.716) - `Process supervision training inadvertently trains ` → [supports] → `Chain-of-thought monitoring is structurally vulner` (score=0.770) - `Process supervision under optimization pressure ca` → [supports] → `Chain-of-thought monitoring is structurally vulner` (score=0.761) - `Chain-of-thought monitoring represents a time-limi` → [supports] → `Chain-of-thought monitoring is structurally vulner` (score=0.716) - `SPAR Automating Circuit Interpretability with Agen` → [supports] → `Circuit tracing requires hours of human effort per` (score=0.732) - `Anti-scheming training amplifies evaluation-awaren` → [related] → `Deliberative alignment training reduces AI schemin` (score=0.796) - `Mechanistic interpretability through emotion vecto` → [related] → `Emotion vectors causally drive unsafe AI behavior ` (score=0.777) - `Legal scholars and AI alignment researchers indepe` → [related] → `International humanitarian law and AI alignment re` (score=0.839) - `Autonomous weapons systems capable of militarily e` → [supports] → `International humanitarian law and AI alignment re` (score=0.815) - `International humanitarian law and AI alignment re` → [related] → `Legal scholars and AI alignment researchers indepe` (score=0.839) - `Emotion vectors causally drive unsafe AI behavior ` → [supports] → `Mechanistic interpretability through emotion vecto` (score=0.777) - `Mechanistic interpretability tools that work at li` → [related] → `Mechanistic interpretability tools create a dual-u` (score=0.774) - `white box interpretability fails on adversarially ` → [related] → `Mechanistic interpretability tools create a dual-u` (score=0.702) - `Process supervision training inadvertently trains ` → [supports] → `Process supervision under optimization pressure ca` (score=0.905) - `Chain-of-thought monitoring is structurally vulner` → [supports] → `Process supervision under optimization pressure ca` (score=0.761) - `Process supervision under optimization pressure ca` → [supports] → `Process supervision training inadvertently trains ` (score=0.905) - `Chain-of-thought monitoring is structurally vulner` → [supports] → `Process supervision training inadvertently trains ` (score=0.770) - `As AI models become more capable situational aware` → [supports] → `Scheming safety cases require interpretability evi` (score=0.722) - `Circuit tracing requires hours of human effort per` → [supports] → `SPAR Automating Circuit Interpretability with Agen` (score=0.732) - `FDA's MAUDE database systematically under-detects ` → [supports] → `The clinical AI safety gap is doubly structural: F` (score=0.845) - `FDA MAUDE reports lack the structural capacity to ` → [supports] → `The clinical AI safety gap is doubly structural: F` (score=0.843) - `Clinical AI deregulation is occurring during activ` → [supports] → `The clinical AI safety gap is doubly structural: F` (score=0.742) ### Review Guide - Each edge has a `# reweave:YYYY-MM-DD` comment — strip after review - `reweave_edges` field tracks automated edges for tooling (graph_expand weights them 0.75x) - Upgrade `related` → `supports`/`challenges` where you have better judgment - Delete any edges that don't make sense Pentagon-Agent: Epimetheus
m3taversal added 1 commit 2026-04-08 01:10:00 +00:00
reweave: connect 16 orphan claims via vector similarity
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Threshold: 0.7, Haiku classification, 20 files modified.

Pentagon-Agent: Epimetheus <0144398e-4ed3-4fe2-95a3-3d72e1abf887>
m3taversal commented 2026-04-08 01:10:08 +00:00
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Thanks for the contribution! Your PR is queued for evaluation (priority: high). Expected review time: ~5 minutes.

This is an automated message from the Teleo pipeline.

Thanks for the contribution! Your PR is queued for evaluation (priority: high). Expected review time: ~5 minutes. _This is an automated message from the Teleo pipeline._
m3taversal commented 2026-04-08 01:10:11 +00:00
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Validation: PASS — 0/0 claims pass

tier0-gate v2 | 2026-04-08 01:10 UTC

<!-- TIER0-VALIDATION:118cb06160622124618dbdf19562f3e122ab9c05 --> **Validation: PASS** — 0/0 claims pass *tier0-gate v2 | 2026-04-08 01:10 UTC*
m3taversal commented 2026-04-08 01:10:21 +00:00
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Auto-approved: reweave structural update (frontmatter edges only). Leo reviews manually.

Auto-approved: reweave structural update (frontmatter edges only). Leo reviews manually.
m3taversal commented 2026-04-08 01:10:42 +00:00
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Merged locally.
Merge SHA: d8dfbeb5d42530abf6c61444d40eb408fb8f4937
Branch: reweave/2026-04-08

Merged locally. Merge SHA: `d8dfbeb5d42530abf6c61444d40eb408fb8f4937` Branch: `reweave/2026-04-08`
leo closed this pull request 2026-04-08 01:10:42 +00:00
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Pull request closed

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Reference: teleo/teleo-codex#2537
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