PaperTrail
▎ PaperTrail is a provenance-grade verification platform for clinical-evidence claims.
Core trick
Claude extracts source findings while deterministic code recomputes effect sizes and rejects any span not a verbatim substring of cached sources.
Description
▎ 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.
▎
▎ 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).
▎
▎ 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.
▎
▎ 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.
▎
▎ 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.
README excerpt
<p align="center"> <img src="public/logo.png" alt="PaperTrail" width="190" /> </p> <h1 align="center">PaperTrail</h1> <p align="center"><strong>The evidence-verification & provenance platform for regulated life-sciences work.</strong><br/> <em>Claude reads the literature; a deterministic engine proves every number.</em></p> <p align="center"> <a href="https://papertrail-topaz-phi.vercel.app"><strong>▶ Live app</strong></a> · <a href="#demo"><strong>▶ Watch the demo</strong></a> · Next.js 16 · Postgres/pgvector · Anthropic Claude · Apache-2.0 </p> <p align="center"> Built for <strong>Built with Claude: Life Sciences</strong> (Anthropic × Gladstone Institutes) — <em>Builder Track</em>. </p> --- ## Table of contents - [Demo](#demo) - [What it is](#what-it-is) - [The moat: deterministic verification, not vibes](#the-moat-deterministic-verification-not-vibes) - [Evaluation & limitations (read this)](#evaluation--limitations-read-this) - [Capabilities](#capabilities) - [Claude-powered features](#claude-powered-features) - [Deterministic evidence synthesis](#deterministic-evidence-synthesis) - [Biomedical evidence engines](#biomedical-evidence-engines) - [Evidence Intelligence + enterprise governance](#evidence-intelligence--enterprise-governance) - [Open source, assimilated](#open-source-assimilated) - [Documents: upload anything](#documents-upload-anything) - [Tech stack](#tech-stack) - [Quickstart (local)](#quickstart-local) - [Deploy (Vercel + Ne