Auto-Detect Bad Science. Correct the Record

The biggest hidden risk in modern AI-assisted research is building on bad foundations. Retractions, image manipulations, and underpowered studies leak into every literature corpus, and once a downstream model has learned from a fraudulent paper, the corruption propagates silently across years of derivative work. The CureForge Scientific Knowledge Audit & Correction Institute is the federation’s epistemic-hygiene layer. Nine specialized AI systems collaborate across continuous monitoring of major retraction databases, fraudulent-image detection of duplication and gel-blot manipulation, statistical-power flagging of underpowered studies, p-hacking detection, anomalous repeat-experiment success-rate detection, automatic correction of every federation knowledge graph that ingested retracted data, federation-wide cross-reference validation, citation-propagation tracking when retracted papers appear in downstream work, and adversarial review of every federation literature claim. The institute is the answer to the question “what if we built our cancer biology on retractions.”

Value proposition:

• Continuous federation-wide retraction and fraud detection
• Automatic correction of downstream knowledge graphs
• Citation-propagation tracking when retractions cascade