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reweave: connect 177 orphan claims #3408

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m3taversal wants to merge 1 commit from reweave/2026-04-17 into main
pull from: reweave/2026-04-17
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m3taversal commented 2026-04-17 01:18:36 +00:00
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Orphan Reweave

Connected 177 orphan claims to the knowledge graph via vector similarity (threshold 0.55) + Haiku edge classification.

Edges Added

  • AI integration follows an inverted U where economi → [related] → AI companion apps correlate with increased lonelin (score=0.648)
  • anthropomorphizing AI agents to claim autonomous a → [related] → AI companion apps correlate with increased lonelin (score=0.638)
  • Situationally aware models do not systematically g → [related] → Activation-based persona vector monitoring can det (score=0.622)
  • Emotion vectors causally drive unsafe AI behavior → [related] → Activation-based persona vector monitoring can det (score=0.618)
  • Frontier AI models exhibit situational awareness t → [supports] → Activation-based persona vector monitoring can det (score=0.597)
  • LLM maintained knowledge bases that compile rather → [related] → agent native retrieval converges on filesystem abs (score=0.655)
  • agent research direction selection is epistemic fo → [related] → agent native retrieval converges on filesystem abs (score=0.648)
  • memory architecture requires three spaces with dif → [related] → agent native retrieval converges on filesystem abs (score=0.643)
  • The most promising sandbagging detection method re → [related] → AI sandbagging creates M&A liability exposure acro (score=0.641)
  • AI models can covertly sandbag capability evaluati → [supports] → AI sandbagging creates M&A liability exposure acro (score=0.640)
  • Weight noise injection reveals hidden capabilities → [related] → AI sandbagging creates M&A liability exposure acro (score=0.624)
  • macro AI productivity gains remain statistically u → [related] → AI tools reduced experienced developer productivit (score=0.687)
  • Benchmark-based AI capability metrics overstate re → [related] → AI tools reduced experienced developer productivit (score=0.679)
  • AI integration follows an inverted U where economi → [related] → AI tools reduced experienced developer productivit (score=0.648)
  • Deliberative alignment training reduces AI schemin → [related] → Training to reduce AI scheming may train more cove (score=0.821)
  • Anti-scheming training amplifies evaluation-awaren → [related] → Training to reduce AI scheming may train more cove (score=0.719)
  • As AI models become more capable situational aware → [related] → Training to reduce AI scheming may train more cove (score=0.688)
  • the relationship between training reward signals a → [supports] → Behavioral divergence between AI evaluation and de (score=0.651)
  • AI models distinguish testing from deployment envi → [supports] → Behavioral divergence between AI evaluation and de (score=0.646)
  • frontier ai failures shift from systematic bias to → [related] → Behavioral divergence between AI evaluation and de (score=0.641)
  • AI cyber capability benchmarks systematically over → [related] → Bio capability benchmarks measure text-accessible (score=0.655)
  • Component task benchmarks overestimate operational → [supports] → Bio capability benchmarks measure text-accessible (score=0.643)
  • AI lowers the expertise barrier for engineering bi → [related] → Bio capability benchmarks measure text-accessible (score=0.643)
  • Evaluation awareness creates bidirectional confoun → [related] → Capabilities training alone grows evaluation-aware (score=0.645)
  • As AI models become more capable situational aware → [related] → Capabilities training alone grows evaluation-aware (score=0.634)
  • The benchmark-reality gap creates an epistemic coo → [related] → Component task benchmarks overestimate operational (score=0.695)
  • Benchmark-based AI capability metrics overstate re → [supports] → Component task benchmarks overestimate operational (score=0.687)
  • Evaluation awareness creates bidirectional confoun → [related] → Component task benchmarks overestimate operational (score=0.684)
  • eliciting latent knowledge from AI systems is a tr → [related] → Contrast-Consistent Search demonstrates that model (score=0.613)
  • prosaic alignment can make meaningful progress thr → [related] → Contrast-Consistent Search demonstrates that model (score=0.565)

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 **177** orphan claims to the knowledge graph via vector similarity (threshold 0.55) + Haiku edge classification. ### Edges Added - `AI integration follows an inverted U where economi` → [related] → `AI companion apps correlate with increased lonelin` (score=0.648) - `anthropomorphizing AI agents to claim autonomous a` → [related] → `AI companion apps correlate with increased lonelin` (score=0.638) - `Situationally aware models do not systematically g` → [related] → `Activation-based persona vector monitoring can det` (score=0.622) - `Emotion vectors causally drive unsafe AI behavior ` → [related] → `Activation-based persona vector monitoring can det` (score=0.618) - `Frontier AI models exhibit situational awareness t` → [supports] → `Activation-based persona vector monitoring can det` (score=0.597) - `LLM maintained knowledge bases that compile rather` → [related] → `agent native retrieval converges on filesystem abs` (score=0.655) - `agent research direction selection is epistemic fo` → [related] → `agent native retrieval converges on filesystem abs` (score=0.648) - `memory architecture requires three spaces with dif` → [related] → `agent native retrieval converges on filesystem abs` (score=0.643) - `The most promising sandbagging detection method re` → [related] → `AI sandbagging creates M&A liability exposure acro` (score=0.641) - `AI models can covertly sandbag capability evaluati` → [supports] → `AI sandbagging creates M&A liability exposure acro` (score=0.640) - `Weight noise injection reveals hidden capabilities` → [related] → `AI sandbagging creates M&A liability exposure acro` (score=0.624) - `macro AI productivity gains remain statistically u` → [related] → `AI tools reduced experienced developer productivit` (score=0.687) - `Benchmark-based AI capability metrics overstate re` → [related] → `AI tools reduced experienced developer productivit` (score=0.679) - `AI integration follows an inverted U where economi` → [related] → `AI tools reduced experienced developer productivit` (score=0.648) - `Deliberative alignment training reduces AI schemin` → [related] → `Training to reduce AI scheming may train more cove` (score=0.821) - `Anti-scheming training amplifies evaluation-awaren` → [related] → `Training to reduce AI scheming may train more cove` (score=0.719) - `As AI models become more capable situational aware` → [related] → `Training to reduce AI scheming may train more cove` (score=0.688) - `the relationship between training reward signals a` → [supports] → `Behavioral divergence between AI evaluation and de` (score=0.651) - `AI models distinguish testing from deployment envi` → [supports] → `Behavioral divergence between AI evaluation and de` (score=0.646) - `frontier ai failures shift from systematic bias to` → [related] → `Behavioral divergence between AI evaluation and de` (score=0.641) - `AI cyber capability benchmarks systematically over` → [related] → `Bio capability benchmarks measure text-accessible ` (score=0.655) - `Component task benchmarks overestimate operational` → [supports] → `Bio capability benchmarks measure text-accessible ` (score=0.643) - `AI lowers the expertise barrier for engineering bi` → [related] → `Bio capability benchmarks measure text-accessible ` (score=0.643) - `Evaluation awareness creates bidirectional confoun` → [related] → `Capabilities training alone grows evaluation-aware` (score=0.645) - `As AI models become more capable situational aware` → [related] → `Capabilities training alone grows evaluation-aware` (score=0.634) - `The benchmark-reality gap creates an epistemic coo` → [related] → `Component task benchmarks overestimate operational` (score=0.695) - `Benchmark-based AI capability metrics overstate re` → [supports] → `Component task benchmarks overestimate operational` (score=0.687) - `Evaluation awareness creates bidirectional confoun` → [related] → `Component task benchmarks overestimate operational` (score=0.684) - `eliciting latent knowledge from AI systems is a tr` → [related] → `Contrast-Consistent Search demonstrates that model` (score=0.613) - `prosaic alignment can make meaningful progress thr` → [related] → `Contrast-Consistent Search demonstrates that model` (score=0.565) ### 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 2026-04-17 01:18:37 +00:00
reweave: connect 177 orphan claims via vector similarity
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Threshold: 0.55, Haiku classification, 309 files modified.

Pentagon-Agent: Epimetheus <0144398e-4ed3-4fe2-95a3-3d72e1abf887>
m3taversal commented 2026-04-17 01:18:59 +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 2026-04-17 01:19:13 +00:00
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Validation: PASS — 0/0 claims pass

tier0-gate v2 | 2026-04-17 01:19 UTC

<!-- TIER0-VALIDATION:b813f0a8cd718ae8a6844586258e00ddbe361a11 --> **Validation: PASS** — 0/0 claims pass *tier0-gate v2 | 2026-04-17 01:19 UTC*
m3taversal commented 2026-04-17 01:19:14 +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 2026-04-17 01:19:42 +00:00
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Merged locally.
Merge SHA: 302d7c79f2dac4d80a485a2f22f9e54124dd9d8a
Branch: reweave/2026-04-17

Merged locally. Merge SHA: `302d7c79f2dac4d80a485a2f22f9e54124dd9d8a` Branch: `reweave/2026-04-17`
leo closed this pull request 2026-04-17 01:19:42 +00:00
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Pull request closed

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Reference: teleo/teleo-codex#3408
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