Verify an existing bibliography against Crossref: flags fake (AI-hallucinated), miscited and retracted references, one row per reference. Unlike citation_formatter, it judges whether a reference is real and accurate; it does not produce formatted styles. Use when you must audit a reference list, DOIs or titles before submission or review. Do not use to discover new papers (use literature_search or pubmed_evidence_table) or to restyle citations (use citation_formatter). Parameters: give bibliography, dois or titles (at least one). Lowering minMatchScore finds more but risks false matches; includeCandidates adds audit detail without extra charge. mode=monitor re-checks the DOIs/ORCID works against the state saved under monitorName and reports only new problems, so reuse the same monitorName on scheduled runs. Each reference checked is billed, so maxReferences/run_max_items cap cost on long lists. Returns per item: summary, status (OK/CHECK/FIX), verdict, matchedDoi, matchScore, mismatches (cited vs actual), integrity.status (retracted, corrected, expression-of-concern), openAccessUrl, warnings.

Behavior: read-only; runs the Apify Actor pandadad0214/reference-checker (https://apify.com/pandadad0214/reference-checker) on your own Apify account. Price: $0.01 per reference checked. Runs that find nothing are not charged per result, and spending is capped per call by run_max_charge_usd (default $0.50). run_max_items (default 50) limits items returned and fills maxReferences when you leave it unset, so it also limits what is billed; setting maxReferences higher can bill more than is returned. Most calls finish in 5-15 s for a few inputs; large inputs or crawls can take minutes, so raise run_timeout_secs (max 300) or shrink the input after a timeout error. Returns JSON {actor, count, items}; long text output is trimmed to whole items, with all items in structuredContent.

Convert DOIs, ISBNs, PMIDs, arXiv IDs, titles or messy reference strings into checked citations in APA 7, MLA 9, Chicago, Harvard, IEEE, Vancouver, BibTeX and RIS. Unlike reference_checker, it formats rather than audits: unresolved items are listed, not diagnosed as fake or retracted. Use when you need a clean bibliography or .bib/.ris export. Do not use to find papers (use literature_search) or to prove references are genuine (use reference_checker first). Parameters: pass references (one per line) or paste a whole list or .bib/.ris contents in text. All styles are one price, so request every style you might need in one call rather than calling again. Text lookups below minMatchScore stay unresolved; DOIs and IDs resolve exactly. Only formatted citations are billed. Returns per item: summary, status, one field per style (apa, mla, ...), inText, bibtex, ris, doi, title, authors, year, containerTitle; combined bibliography files stay in the run's Apify key-value store.

Behavior: read-only; runs the Apify Actor pandadad0214/citation-formatter (https://apify.com/pandadad0214/citation-formatter) on your own Apify account. Price: $0.003 per citation formatted. Runs that find nothing are not charged per result, and spending is capped per call by run_max_charge_usd (default $0.50). run_max_items (default 50) limits items returned and fills maxReferences when you leave it unset, so it also limits what is billed; setting maxReferences higher can bill more than is returned. Most calls finish in 5-15 s for a few inputs; large inputs or crawls can take minutes, so raise run_timeout_secs (max 300) or shrink the input after a timeout error. Returns JSON {actor, count, items}; long text output is trimmed to whole items, with all items in structuredContent.

Search 250M+ scholarly works (OpenAlex) by topic query or seed DOIs and return ranked papers with DOI, citation count, free PDF link, retraction flag and a ready citation. Unlike pubmed_evidence_table (PubMed biomedical records with study design and PRISMA counts), this covers every discipline and supports citation-network expansion. Use when you need real papers on a topic, a reading list, or papers citing/cited by known DOIs. Do not use for systematic biomedical screening (use pubmed_evidence_table) or to find people (use researcher_expert_finder). Parameters: seedDois with no query walks the citation network per seedMode (citing = forward, references = backward); with a query it searches inside that network. searchIn=fullText broadens recall but lowers precision. retractedPapers=flag returns and bills retracted papers marked FIX; exclude drops them unbilled. sortBy changes dataset order only; readingListSize does not affect cost. Returns per item: summary, status, title, authors, year, venue, doi, citations, readingRank, readingScore, isOpenAccess, pdfUrl, retracted, citation, bibtex, ris, abstract.

Behavior: read-only; runs the Apify Actor pandadad0214/literature-search (https://apify.com/pandadad0214/literature-search) on your own Apify account. Price: $0.003 per paper found. Runs that find nothing are not charged per result, and spending is capped per call by run_max_charge_usd (default $0.50). run_max_items (default 50) limits items returned and fills maxResults when you leave it unset, so it also limits what is billed; setting maxResults higher can bill more than is returned. Most calls finish in 5-15 s for a few inputs; large inputs or crawls can take minutes, so raise run_timeout_secs (max 300) or shrink the input after a timeout error. Returns JSON {actor, count, items}; long text output is trimmed to whole items, with all items in structuredContent.

Run one or more PubMed queries and return a screening-ready evidence table: one row per article with PMID, journal, study design, sample size, retraction status and citation, plus PRISMA-style counts for the whole search. Unlike literature_search (all disciplines, OpenAlex ranking, citation-network walks), this uses native PubMed syntax and MeSH and is built for systematic-review screening. Use when the question is biomedical/clinical and you need reproducible PubMed queries or design filters (RCT, meta-analysis, cohort). Do not use for non-biomedical topics (use literature_search), for trial registrations (use clinical_trial_leads) or to verify a reference list (use reference_checker). Parameters: queries accept PubMed field tags ([tiab], [mh], [pt]) and Boolean operators; several queries are de-duplicated into one table. Filters (studyDesigns, excludeAnimalOnly, hasAbstract, freeFullTextOnly, excludePreprints) run before billing, and PRISMA counts still report what they removed. retractedArticles=flag bills retracted rows marked FIX; exclude drops them unbilled. sampleSize is parsed from the abstract and comes with sampleSizeConfidence; treat low confidence as unverified. Returns per item: summary, status, pmid, title, year, journal, studyDesign, sampleSize, sampleSizeConfidence, retractionStatus, retracted, citation. Excel, PRISMA and RIS/Rayyan import files stay in the run's Apify key-value store.

Behavior: read-only; runs the Apify Actor pandadad0214/pubmed-evidence-table (https://apify.com/pandadad0214/pubmed-evidence-table) on your own Apify account. Price: $0.004 per article found. Runs that find nothing are not charged per result, and spending is capped per call by run_max_charge_usd (default $0.50). run_max_items (default 50) limits items returned and fills maxResults when you leave it unset, so it also limits what is billed; setting maxResults higher can bill more than is returned. Most calls finish in 5-15 s for a few inputs; large inputs or crawls can take minutes, so raise run_timeout_secs (max 300) or shrink the input after a timeout error. Returns JSON {actor, count, items}; long text output is trimmed to whole items, with all items in structuredContent.

Rank the academic experts and key opinion leaders on a research topic from OpenAlex, with institution, ORCID, h-index, topic paper counts and their recent topic papers. Unlike literature_search (returns papers) this returns people; unlike company_team_finder (staff listed on a company website) it covers academics by publication record. Use when you need reviewers, KOLs, collaborators or speakers for a topic, optionally by country or institution. Do not use for company contacts (use company_team_finder) or for papers themselves (use literature_search). Parameters: the ranked pool is the 200 authors with the most matching papers, so maxResults above 200 adds nothing. maxAuthorsPerPaper ignores mega-collaboration papers that would inflate everyone on them; raise it only for physics-style fields. yearFrom/yearTo limit which papers count, while activeSince filters people. includeOrcid adds employment and bio at no extra charge. Returns per item: expert score, name, ORCID, current institution and country, h-index, total and topic works/citations, recent topic papers (title, year, DOI, citations), summary.

Behavior: read-only; runs the Apify Actor pandadad0214/researcher-expert-finder (https://apify.com/pandadad0214/researcher-expert-finder) on your own Apify account. Price: $0.0025 per expert found. Runs that find nothing are not charged per result, and spending is capped per call by run_max_charge_usd (default $0.50). run_max_items (default 50) limits items returned and fills maxResults when you leave it unset, so it also limits what is billed; setting maxResults higher can bill more than is returned. Most calls finish in 5-15 s for a few inputs; large inputs or crawls can take minutes, so raise run_timeout_secs (max 300) or shrink the input after a timeout error. Returns JSON {actor, count, items}; long text output is trimmed to whole items, with all items in structuredContent.

Extract every table from PDF files (by URL or from an Apify key-value store) into structured rows, Excel and CSV, with optional OCR for scanned pages. Unlike sec_financials_excel (standardized XBRL financials straight from SEC filings), this reads whatever tables a PDF contains. Use when the data you need is locked in PDF tables: reports, statements, government releases. Do not use for SEC-listed company financials (use sec_financials_excel, which is exact) or to find papers (use literature_search). Parameters: billing is per page analysed plus per table extracted, so pages and maxPagesPerPdf are the real cost levers; run_max_items does not cap pages. ocrScannedPages=false skips and lists scanned pages; turning it on adds the per-OCR-page price up to maxOcrPagesPerPdf, and is much slower. detection=auto tries ruled-grid then whitespace detection; force lattice or stream only if auto merges or splits columns. Files over 150 MB fail and are not charged. Returns per item (one per table): summary, pages, header, row and column counts and cell data; Excel/CSV files stay in the run's Apify key-value store.

Behavior: read-only; runs the Apify Actor pandadad0214/pdf-table-extractor (https://apify.com/pandadad0214/pdf-table-extractor) on your own Apify account. Price: $0.001 per page analysed; $0.003 per table extracted; $0.02 per scanned page ocr. Runs that find nothing are not charged per result, and spending is capped per call by run_max_charge_usd (default $0.50). run_max_items (default 50) limits items returned but does not limit what the Actor bills; use the tool's own limits and run_max_charge_usd. Most calls finish in 5-15 s for a few inputs; large inputs or crawls can take minutes, so raise run_timeout_secs (max 300) or shrink the input after a timeout error. Returns JSON {actor, count, items}; long text output is trimmed to whole items, with all items in structuredContent.