# Metavert

- **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:** [Jon Radoff](https://cerebralvalley.ai/u/jradoff)
- **GitHub:** https://github.com/jonradoff/aitiome
- **Demo video:** https://www.youtube.com/watch?v=wZ7HyH8nqFM&feature=youtu.be
- **Gallery:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery/138

Aitiome grades whether an environmental chemical has mechanistically-supported links to Parkinson's or Alzheimer's. Give it a chemical and it reconstructs the OECD-endorsed causal pathway (MIE→KE→AO), grounds each edge in queryable evidence, and grades it on curated evidence — never bioactivity, with calibrated confidence. On a curated adversarial benchmark it recovers 13/13 PD and 12/12 AD known neurotoxicants and rejects 6/6 mitochondria-active decoys with zero errors. The key finding, computed live from our own data: bioactivity is anti-diagnostic — every activity signal separating real neurotoxicants from decoys is at or below chance, while the curated rule is perfect. It ships the discovery limits as an honest map, adds a wet-lab candidate-triage queue, and exposes the whole engine over MCP for agents. It also includes a methods study: adversarial RLM surfaced ~10× more counter-evidence than RAG.

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Markdown version of https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery/138. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt