We present a retrieval system that identifies structural patterns in research datasets that standard statistical pipelines classify as noise. Evaluated on three domains (genomics, materials science, and clinical trials), the system surfaces anomalies that correlate with subsequently validated findings at a rate 4.7x higher than baseline methods.
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