openalex-high-impact-research

Use a structured OpenAlex workflow to retrieve citable papers, extract atomic claims, generate testable hypotheses, and detect contradictions with provenance. It targets a defined research domain using topic-aligned filters to build a structured evidence base.

Finding high-impact literature with OpenAlex citation data requires applying a citation floor and topic-aligned filters. This workflow shortlists citable papers, scores relevance, and provides abstract-level evidence when available to support a structured evidence base.

Yes, you can persist OpenAlex search results to MongoDB. This workflow saves a complete run document including the shortlist, atomic claims, hypotheses, and reasoning steps to MongoDB for end-to-end traceability and later analysis.

Detect contradictions in academic papers by running a structured reasoning pipeline over high-impact OpenAlex literature. The workflow extracts atomic claims, generates testable hypotheses, and identifies contradictions while maintaining provenance for the reasoning steps.

MongoDB is required to achieve end-to-end persistence and auditability. The workflow saves one complete run document containing the shortlist and reasoning steps to MongoDB, ensuring reproducible OpenAlex retrieval and traceability for later analysis.