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# Self-Audit Report: Vida
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**Date:** 2026-03-16
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**Domain:** health
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**Claims audited:** 44
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**Overall status:** WARNING
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---
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## Structural Findings
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### Schema Compliance: PASS
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- 44/44 files have all required frontmatter (type, domain, description, confidence, source, created)
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- 44/44 descriptions add meaningful context beyond the title
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- 3 files use non-standard extended fields (last_evaluated, depends_on, challenged_by, secondary_domains, tradition) — these are useful extensions but should be documented in schemas/claim.md if adopted collectively
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### Orphan Ratio: CRITICAL — 74% (threshold: 15%)
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- 35 of 47 health claims have zero incoming wiki links from other claims or agent files
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- All 12 "connected" claims receive links only from inbox/archive source files, not from the knowledge graph
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- **This means the health domain is structurally isolated.** Claims link out to each other internally, but no other domain or agent file links INTO health claims.
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**Classification of orphans:**
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- 15 AI/technology claims — should connect to ai-alignment domain
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- 8 business/market claims — should connect to internet-finance, teleological-economics
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- 8 policy/structural claims — should connect to mechanisms, living-capital
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- 4 foundational claims — should connect to critical-systems, cultural-dynamics
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**Root cause:** Extraction-heavy, integration-light. Claims were batch-extracted (22 on Feb 17 alone) without a corresponding integration pass to embed them in the cross-domain graph.
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### Link Health: PASS
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- No broken wiki links detected in claim bodies
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- All `[[wiki links]]` resolve to existing files
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### Staleness: PASS (with caveat)
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- All claims created within the last 30 days (domain is new)
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- However, 22/44 claims cite evidence from a single source batch (Bessemer State of Health AI 2026). Source diversity is healthy at the domain level but thin at the claim level.
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### Duplicate Detection: PASS
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- No semantic duplicates found
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- Two near-pairs worth monitoring:
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- "AI diagnostic triage achieves 97% sensitivity..." and "medical LLM benchmark performance does not translate to clinical impact..." — not duplicates but their tension should be explicit
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- "PACE demonstrates integrated care averts institutionalization..." and "PACE restructures costs from acute to chronic..." — complementary, not duplicates
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---
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## Epistemic Findings
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### Unacknowledged Contradictions: 3 (HIGH PRIORITY)
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**1. Prevention Economics Paradox**
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- Claim: "the healthcare attractor state...profits from health rather than sickness" (likely)
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- Claim: "PACE restructures costs from acute to chronic spending WITHOUT REDUCING TOTAL EXPENDITURE" (likely)
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- PACE is the closest real-world approximation of the attractor state (100% capitation, fully integrated, community-based). It shows quality/outcome improvement but cost-neutral economics. The attractor state thesis assumes prevention is profitable. PACE says it isn't — the value is clinical and social, not financial.
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- **The attractor claim's body addresses this briefly but the tension is buried, not explicit in either claim's frontmatter.**
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**2. Jevons Paradox vs AI-Enabled Prevention**
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- Claim: "healthcare AI creates a Jevons paradox because adding capacity to sick care induces more demand" (likely)
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- Claim: "the healthcare attractor state" relies on "AI-augmented care delivery" for prevention
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- The Jevons claim asserts ALL healthcare AI optimizes sick care. The attractor state assumes AI can optimize prevention. Neither acknowledges the other.
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**3. Cost Curve vs Attractor State Timeline**
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- Claim: "the healthcare cost curve bends UP through 2035" (likely)
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- Claim: "GLP-1s...net cost impact inflationary through 2035" (likely)
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- Claim: attractor state assumes prevention profitability
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- If costs are structurally inflationary through 2035, the prevention-first attractor can't achieve financial sustainability during the transition period. This timeline constraint isn't acknowledged.
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### Confidence Miscalibrations: 3
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**Overconfident (should downgrade):**
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1. "Big Food companies engineer addictive products by hacking evolutionary reward pathways" — rated `proven`, should be `likely`. The business practices are evidenced but "intentional hacking" of reward pathways is interpretation, not empirically proven via RCT.
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2. "AI scribes reached 92% provider adoption" — rated `proven`, should be `likely`. The 92% figure is "deploying, implementing, or piloting" (Bessemer), not proven adoption. The causal "because" clause is inferred.
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3. "CMS 2027 chart review exclusion targets vertical integration profit arbitrage" — rated `proven`, should be `likely`. CMS intent is inferred from policy mechanics, not explicitly documented.
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**Underconfident (could upgrade):**
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1. "consumer willingness to pay out of pocket for AI-enhanced care" — rated `likely`, could be `proven`. RadNet study (N=747,604) showing 36% choosing $40 AI premium is large-scale empirical market behavior data.
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### Belief Grounding: WARNING
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- Belief 1 ("healthspan is the binding constraint") — well-grounded in 7+ claims
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- Belief 2 ("80-90% of health outcomes are non-clinical") — grounded in `medical care explains 10-20%` (proven) but THIN on what actually works to change behavior. Only 1 claim touches SDOH interventions, 1 on social isolation. No claims on community health workers, social prescribing mechanisms, or behavioral economics of health.
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- Belief 3 ("structural misalignment") — well-grounded in CMS, payvidor, VBC claims
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- Belief 4 ("atoms-to-bits") — grounded in wearables + Function Health claims
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- Belief 5 ("clinical AI + safety risks") — grounded in human-in-the-loop degradation, benchmark vs clinical impact. But thin on real-world deployment safety data.
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### Scope Issues: 3
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1. "AI-first screening viable for ALL imaging and pathology" — evidence covers 14 CT conditions and radiology, not all imaging/pathology modalities. Universal is unwarranted.
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2. "the physician role SHIFTS from information processor to relationship manager" — stated as completed fact; evidence shows directional trend, not completed transformation.
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3. "the healthcare attractor state...PROFITS from health" — financial profitability language is stronger than PACE evidence supports. "Incentivizes health" would be more accurate.
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---
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## Knowledge Gaps (ranked by impact on beliefs)
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1. **Behavioral health infrastructure mechanisms** — Belief 2 depends on non-clinical interventions working at scale. Almost no claims about WHAT works: community health worker programs, social prescribing, digital therapeutics for behavior change. This is the single biggest gap.
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2. **International/comparative health systems** — Zero non-US claims. Singapore 3M, Costa Rica EBAIS, Japan LTCI, NHS England are all in the archive but unprocessed. Limits the generalizability of every structural claim.
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3. **GLP-1 second-order economics** — One claim on market size. Nothing on: adherence at scale, insurance coverage dynamics, impact on bariatric surgery demand, manufacturing bottlenecks, Novo/Lilly duopoly dynamics.
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4. **Clinical AI real-world safety data** — Belief 5 claims safety risks but evidence is thin. Need: deployment accuracy vs benchmark, alert fatigue rates, liability incidents, autonomous diagnosis failure modes.
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5. **Space health** — Zero claims. Cross-domain bridge to Astra is completely unbuilt. Radiation biology, bone density, psychological isolation — all relevant to both space medicine and terrestrial health.
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6. **Health narratives and meaning** — Cross-domain bridge to Clay is unbuilt. Placebo mechanisms, narrative identity in chronic illness, meaning-making as health intervention.
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---
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## Cross-Domain Health
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- **Internal linkage:** Dense — most health claims link to 2-5 other health claims
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- **Cross-domain linkage ratio:** ~5% (CRITICAL — threshold is 15%)
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- **Missing connections:**
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- health ↔ ai-alignment: 15 AI-related health claims, zero links to Theseus's domain
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- health ↔ internet-finance: VBC/CMS/GLP-1 economics claims, zero links to Rio's domain
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- health ↔ critical-systems: "healthcare is a complex adaptive system" claim, zero links to foundations/critical-systems/
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- health ↔ cultural-dynamics: deaths of despair, modernization claims, zero links to foundations/cultural-dynamics/
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- health ↔ space-development: zero claims, zero links
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---
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## Recommended Actions (prioritized)
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### Critical
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1. **Resolve prevention economics contradiction** — Add `challenged_by` to attractor state claim pointing to PACE cost evidence. Consider new claim: "prevention-first care models improve quality without reducing total costs during transition, making the financial case dependent on regulatory and payment reform rather than inherent efficiency"
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2. **Address Jevons-prevention tension** — Either scope the Jevons claim ("AI applied to SICK CARE creates Jevons paradox") or explain the mechanism by which prevention-oriented AI avoids the paradox
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3. **Integration pass** — Batch PR adding incoming wiki links from core/, foundations/, and other domains/ to the 35 orphan claims. This is the highest-impact structural fix.
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### High
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4. **Downgrade 3 confidence levels** — Big Food (proven→likely), AI scribes (proven→likely), CMS chart review (proven→likely)
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5. **Scope 3 universals** — AI diagnostic triage ("CT and radiology" not "all"), physician role ("shifting toward" not "shifts"), attractor state ("incentivizes" not "profits from")
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6. **Upgrade 1 confidence level** — Consumer willingness to pay (likely→proven)
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### Medium
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7. **Fill Belief 2 gap** — Extract behavioral health infrastructure claims from existing archive sources
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8. **Build cross-domain links** — Start with health↔ai-alignment (15 natural connection points) and health↔critical-systems (complex adaptive system claim)
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---
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*This report was generated using the self-audit skill (skills/self-audit.md). First audit of the health domain.*
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