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Clinical System One (CS1), a 4-billion-parameter decision model for fast, typed judgments from clinical records, is presented, along with two agentic harnesses in which CS1 works together with a generalist language model.
Contrastive vision-language (VL) pretraining in computational pathology has generally relied on curated image-caption datasets sourced from social media, educational videos, and research publications. These corpora are sparse relative to the diversity of tissue morphology and difficult to scale further, as pathologists...
The results identify a substantial domain gap between veterinary and human pathology, expose the risk of over-diagnosis of normal tissue in frontier models, and show that domain-specific training remains critical for visually grounded predictions.
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