AI that reads the unpublished: a three-layer protocol flags four blind spots in CPEB biology and yields a testable sleep-forgetting hypothesis
AI systems for scientific discovery usually learn only from published positive results, leaving them structurally blind to failures and suppressed directions. A three-layer operational protocol turns that gap into executable steps: it scores theoretically possible but undocumented relationships in a knowledge graph, uses an adversarial classifier to surface features systematically suppressed in unpublished, rejected or failed data, and generates hypotheses that diverge from consensus yet pass viability filters. In a CPEB3/CPEB4 neurobiology case, it flagged four structural blind spots and produced a testable hypothesis about astrocytic translation during sleep and active forgetting.