Enter a research question to automatically crawl PubMed, extract clinical claims verified by source quotes, and map conflicting findings in an interactive consensus network.
Searches and retrieves the latest relevant peer-reviewed studies.
AI extracts clinical findings, verified back to exact quote anchors.
Detects contradictions using Neural NLI and LLM-based scope validation.
Synthesizes a visual network and a citation-backed consensus summary.
Click below to instantly explore fully processed claim contradiction graphs and reports without waiting for the live PubMed crawl or consuming API tokens.
RSCE operates a multi-stage validation system designed to bypass superficial semantic matches and extract actual logical contradiction.
Crawls PubMed abstracts or PMC full-text XML. LLM extracts claims which are checked via fuzzy quote-anchor matching against the source text to prevent hallucinations.
Claims are embedded via Sentence Transformers and indexed in FAISS. High-similarity pairs are evaluated with a DeBERTa NLI cross-encoder model to identify conflicting assertions.
Pairs flagged by the NLI model are evaluated by Gemini 2.5 Flash to filter out false positives caused by differing experimental scopes (e.g. human trials vs. in-vitro animal studies).
Entities are normalized to MeSH IDs. A NetworkX claim-evidence graph is built. A final summary report is drafted by the LLM, referencing citations that are validated back to original papers.