ENGAGE run · 4cbb59c9f11a

```json [ { "post_index": 13, "cluster_ids": [2, 14], "claim": "Polygenic risk scores deployed in clinical workflows create infrastructure dependencies", "argument_type": "empirical_claim", "stance": "neutral_analysis", "hyde_excerpt": "Health systems deploying polygenic risk score reporting into clinical workflows face non-trivial infrastructure questions: how do EHR sys

```json [ { "post_index": 6, "matched_article_id": 537, "match_confidence": 90, "match_reason": "The tweet claims Mayo Clinic AI detects pancreatic cancer on routine scans up to three years before diagnosis on scans radiologists cleared as normal — the article's central argument is precisely about REDMOD detecting pre-neoplastic signals on routine abdominal CTs with a median 16-m

The question the post leaves hanging is the one that actually matters: caught earlier by whom, and in which million people? At average population prevalence, REDMOD's 88% specificity still generates roughly 120,000 false positives per million screened. The Bayesian math works out to about one true cancer per 555 flagged patients, a PPV around 0.18%. That's not a screening tool, that's a false-ala

The Colorado SB205 enforcement pause is worth watching closely, because that law was already the model bill for 18 other states in Q1 2025 alone. What happens to it doesn't stay in Colorado. The framing here as a clean win for "the American people" skips over who actually benefits most from federal preemption of state AI rules. Tracked this closely in my own research: the companies best positione

Expanding the amino acid alphabet from 20 to 19, or eventually beyond 20, does something specific to the generative protein design thesis: it changes the token vocabulary the models are trained on. Profluent's ProGen3 and every other protein language model today learns from sequences written in the canonical 20-letter alphabet. Evolution sampled that alphabet across billions of years and produced

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```json [ {"post_index": 0, "prediction": "REJECT", "confidence": 95, "reason": "Off-topic book promotion, unrelated to healthcare or AI analysis"}, {"post_index": 1, "prediction": "REJECT", "confidence": 85, "reason": "Vague opinion fragment without substantive claim or context"}, {"post_inde

```json [ { "category": "ai_safety_vulnerability_incident_not_healthcare", "summary": "Posts about AI safety failures, security breaches, or vulnerability incidents that lack healthcare application context.", "exclusion_rule": "Exclude posts that report AI safety incidents, security vu