open-access-mining-guide

Automate full-text extraction by running a pipeline that queries OA sources like PMC and arXiv, parses the documents, and performs section-aware extraction for methods and results. It targets corpus-scale mining and returns structured, provenance-backed outputs.

Build reproducible literature mining pipelines by defining an OA corpus query, executing the retrieval and parsing stages, and exporting the structured data with provenance directly into Zotero notes and collections for synthesis.

Yes, section-aware extraction isolates specific parts like methods, results, and discussion from PMC, Europe PMC, CORE, and arXiv documents. This enables targeted corpus-scale mining while maintaining a structured data model with per-paper metadata.

Yes, open-access mining enforces licensing guardrails during corpus-scale retrieval and parsing. It provides a minimum data model and QA-driven curation to ensure compliant, structured outputs with provenance back to Zotero.

Export structured datasets by completing the QA-driven curation of your retrieved OA corpus. The pipeline automatically links per-paper metadata and provenance back to Zotero notes, enabling immediate synthesis and reporting.

Use a dedicated OA mining pipeline when processing corpus-scale volumes across sources like CORE and Europe PMC, as manual review cannot enforce licensing guardrails, automate section-aware extraction, or generate provenance-backed structured outputs.