// Project brief
CapyMatch pre-screens patients for clinical trials. Given a patient note and a ClinicalTrials.gov record, it decides whether the patient is eligible, excluded, or not relevant, and explains the criterion that decided it. We fine-tuned NVIDIA Nemotron 3.5 Super VL with LoRA on 9,000 expert-judged patient–trial pairs using Fireworks serverless training, and run NVIDIA Nemotron 3 Ultra on Fireworks to write a one-line reason for the coordinator. On 900 held-out pairs from 50 patients the model never saw, CapyMatch is the most accurate system we tested: 74.1%. That is statistically tied with OpenAI's flagship GPT-6.1 Sol (72.1%) at about a quarter of the cost, and significantly ahead of GPT-6 Luna, Nemotron 3 Ultra, and its own zero-shot base.
