# PaperTrail

- **Event:** [Built with Claude: Life Sciences](https://cerebralvalley.ai/e/built-with-claude-life-sciences)
- **When:** Jul 7 at 12:00 PM – Jul 14 at 12:00 AM (EDT)
- **Where:** Online
- **Team:** [arhan subasi](https://cerebralvalley.ai/u/arhansuba)
- **GitHub:** https://github.com/caelum0x/papertrail
- **Demo video:** https://youtu.be/K1JPQiUIjWE
- **Gallery:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery/8

▎ PaperTrail is a provenance-grade verification platform for clinical-evidence claims. Given a claim like "lecanemab caused brain swelling in 21.3% of patients," it retrieves the primary source (PubMed / ClinicalTrials.gov), extracts the actual finding, recomputes the effect size deterministically, and flags exactly where the claim diverges — with a trust score and a citation trail where every flagged span maps to a verbatim substring of the cached source.
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▎ The core design decision: deterministic math decides every verdict; Claude only writes grounded language and routing hints — it is never in the numeric or scoring path. The grounding guarantee is enforced as a code invariant (an audit ran 500k+ adversarial fuzz iterations and could not produce an unsourced span).
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▎ Three named-user tools sit on top: Verify a claim, a Lab Notebook that turns dictated bench notes into a grounded, reproducible experiment record (nothing it can't quote is kept), and a Trial Matcher that assesses a de-identified patient against ClinicalTrials.gov criterion-by-criterion. A Mixture-of-Agents pipeline composes 20+ engines (MiniCheck, cross-source aggregation, PyMARE pooling, a discrepancy auditor, STORM debate) into one deterministic verdict.
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▎ What I found (honest): on a single-source clinical benchmark the deterministic + audit path beats a plain Claude call 95% vs 90%; on contested multi-source claims it ties at 100% but stays 87% accurate when the API is down (Claude-alone: 0%). I then audited the entire statistical core (~18 modules — meta-analysis, GRADE, survival, network-meta, fragility, pharmacovigilance) against the biostatistics literature and fixed real correctness bugs: a confidence-interval false-positive on the verify path, a 2× trial-sequential error, a fragility-index bug that inverted "fragile" and "robust," and negation-parity bugs that flipped support↔refute.
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▎ Why it matters: a translational researcher or medical-affairs reviewer must produce and defend numbers. A hallucinating LLM can't be trusted for that. PaperTrail's verdicts are deterministic and every claim traces back to its primary source — provenance, not opinion.

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Markdown version of https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery/8. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt