{"uid":"cap_uNR3Qz3ntQIN_EFS3KxAl","slug":"fittings-citation-extractor-4f463862","name":"fittings Citation Extractor","description":"Pulls DOIs, arXiv ids, PMIDs, PMCIDs and ISBNs out of free text, deduplicated and normalized, with the character offset of each first occurrence.","url":"https://fittings.sh/v1/text/extract-citations?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"text":{"type":"string","description":"Free text, up to 200000 characters"},"kinds":{"type":"array","description":"Restrict to these kinds: doi, arxiv, pmid, pmcid, isbn. Default all."}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.007","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.007/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.007","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.007","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_nrXiarQSE55DhdiqA1Lr7","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.007","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Extracts and normalizes DOIs, arXiv IDs, PMIDs, PMCIDs, and ISBNs from free text, returning deduplicated identifiers with their character offsets.","exampleAgentPrompt":"Can you pull out all the DOIs, arXiv IDs, and ISBNs from this paragraph and tell me where each one first appears? Here's the text: 'See Smith et al. (doi:10.1038/nature12373) and also arXiv:1706.03762 for background.'","exampleUseCases":[{"title":"Literature review citation harvesting","prompt":"I have this 5000-word literature review section — can you extract every DOI and PMID mentioned in it and give me a deduplicated list with the position of each first occurrence?"},{"title":"Reference list ISBN extraction","prompt":"Here's a bibliography from a book chapter. Can you pull out all the ISBNs mentioned in it and normalize them for me?"},{"title":"Preprint mention detection in blog post","prompt":"I want to find every arXiv ID and DOI cited in this blog post text so I can build a reading list. Can you extract only those two types from it?"}],"resultDescription":"A list of deduplicated, normalized citation identifiers found in the input text, each with its type (doi, arxiv, pmid, pmcid, isbn), normalized value, and the character offset of its first occurrence in the source text.","failureModes":["Text exceeds 200,000 character limit — request rejected","Invalid citation kind specified in 'kinds' array — may return error or empty results","Text contains no recognizable citation identifiers — returns empty list","Malformed or ambiguous identifiers in text may be missed or incorrectly normalized"],"whenToPreferThis":"Use this endpoint when you need to reliably parse multiple citation identifier types (DOIs, arXiv IDs, PMIDs, PMCIDs, ISBNs) from unstructured text in a single call with deduplication and offset tracking. It's ideal over regex-based approaches when you need normalization and multi-format support simultaneously, and preferable to general NLP tools when the goal is specifically academic/bibliographic identifier extraction.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-11T18:40:30.788Z","isFirstParty":false,"canonicalSlug":"fittings-citation-extractor-4f463862"}