extract: 2026-03-19-vida-clinical-ai-verification-bandwidth-health-risk

Pentagon-Agent: Epimetheus <968B2991-E2DF-4006-B962-F5B0A0CC8ACA>

inbox/queue/.extraction-debug/2026-03-19-vida-clinical-ai-verification-bandwidth-health-risk.json

@@ -0,0 +1,37 @@
+{
+  "rejected_claims": [
+    {
+      "filename": "clinical-ai-deskilling-creates-compounding-verification-bandwidth-collapse-at-population-scale.md",
+      "issues": [
+        "missing_attribution_extractor"
+      ]
+    },
+    {
+      "filename": "mandatory-ai-practice-drills-are-the-missing-institutional-mechanism-for-clinical-ai-deskilling.md",
+      "issues": [
+        "missing_attribution_extractor"
+      ]
+    }
+  ],
+  "validation_stats": {
+    "total": 2,
+    "kept": 0,
+    "fixed": 7,
+    "rejected": 2,
+    "fixes_applied": [
+      "clinical-ai-deskilling-creates-compounding-verification-bandwidth-collapse-at-population-scale.md:set_created:2026-03-19",
+      "clinical-ai-deskilling-creates-compounding-verification-bandwidth-collapse-at-population-scale.md:stripped_wiki_link:human-in-the-loop-clinical-AI-degrades-to-worse-than-AI-alon",
+      "clinical-ai-deskilling-creates-compounding-verification-bandwidth-collapse-at-population-scale.md:stripped_wiki_link:healthcare-AI-regulation-needs-blank-sheet-redesign-because-",
+      "clinical-ai-deskilling-creates-compounding-verification-bandwidth-collapse-at-population-scale.md:stripped_wiki_link:OpenEvidence-became-the-fastest-adopted-clinical-technology-",
+      "mandatory-ai-practice-drills-are-the-missing-institutional-mechanism-for-clinical-ai-deskilling.md:set_created:2026-03-19",
+      "mandatory-ai-practice-drills-are-the-missing-institutional-mechanism-for-clinical-ai-deskilling.md:stripped_wiki_link:human-in-the-loop-clinical-AI-degrades-to-worse-than-AI-alon",
+      "mandatory-ai-practice-drills-are-the-missing-institutional-mechanism-for-clinical-ai-deskilling.md:stripped_wiki_link:healthcare-AI-regulation-needs-blank-sheet-redesign-because-"
+    ],
+    "rejections": [
+      "clinical-ai-deskilling-creates-compounding-verification-bandwidth-collapse-at-population-scale.md:missing_attribution_extractor",
+      "mandatory-ai-practice-drills-are-the-missing-institutional-mechanism-for-clinical-ai-deskilling.md:missing_attribution_extractor"
+    ]
+  },
+  "model": "anthropic/claude-sonnet-4.5",
+  "date": "2026-03-19"
+}

inbox/queue/2026-03-19-vida-clinical-ai-verification-bandwidth-health-risk.md

@@ -7,10 +7,14 @@ date: 2026-03-19
 domain: health
 secondary_domains: [ai-alignment]
 format: synthesis
-status: unprocessed
+status: null-result
 priority: high
 tags: [clinical-ai, verification-bandwidth, deskilling, openevidence, scale-risk, outcomes-gap, health-ai-safety]
 flagged_for_theseus: ["The verification bandwidth problem in clinical AI is the health-specific instance of Catalini's general Measurability Gap — both should be cross-referenced in the AI safety literature"]
+processed_by: vida
+processed_date: 2026-03-19
+extraction_model: "anthropic/claude-sonnet-4.5"
+extraction_notes: "LLM returned 2 claims, 2 rejected by validator"
 ---
 
 ## Content
@@ -80,3 +84,14 @@ PRIMARY CONNECTION: [[human-in-the-loop clinical AI degrades to worse-than-AI-al
 WHY ARCHIVED: This synthesis identifies a structural mechanism (Catalini Measurability Gap + clinical deskilling + AI scale) that doesn't appear in any individual source but emerges from reading them together. The scale asymmetry at 20M consultations/month makes this a population-health priority, not a clinical curiosity.
 
 EXTRACTION HINT: Extract the compounding risk mechanism as a new claim. Do not extract the individual components (deskilling, benchmark-outcomes gap, etc.) — those already exist in KB. Extract specifically the SCALE MECHANISM that makes them dangerous in combination.
+
+
+## Key Facts
+- OpenEvidence reached 20M clinical consultations per month by January 2026
+- OpenEvidence processed 1M consultations in a single day on March 10, 2026
+- OpenEvidence achieved USMLE 100% benchmark score
+- OpenEvidence valued at $12B as of March 2026
+- OpenEvidence used across 10,000+ hospitals
+- 44% of physicians remain concerned about OpenEvidence accuracy despite heavy use
+- Endoscopists using AI for polyp detection: adenoma detection rate dropped from 28% to 22% when AI was turned off (Hosanagar/Lancet Gastroenterology 2023)
+- Zero peer-reviewed outcomes data for OpenEvidence at 20M consultation/month scale