Scholarly influence metrics for a paper with a derived verdict API

Turn a paper reference into a defensible influence read. Accepts a DOI, an arXiv id, an OpenAlex id, or a free-text title, resolves it via OpenAlex (keyless, ~250M works), and returns NORMALIZED scholarly-impact metrics plus a derived verdict — citation count, citations-per-year velocity, FWCI (field-weighted citation impact), citation percentile (top-1%/top-10% flags), referenced-works count, venue, year, authors, open-access status and OA url, and top concepts/topics — collapsed into an influence label the caller can branch on: highly_cited, above_average, emerging, or low, with the reasons behind it. Distinct from a raw record lookup: it adds the field-aware verdict and falls back to citation velocity when OpenAlex has not yet computed a percentile (e.g. fresh preprints). Answers 'How influential is this paper?', 'Is this paper highly cited for its field?', 'What is this paper's FWCI and citation percentile?', 'Is this a foundational or an emerging work?'.

Price$0.16per request

MethodPOST

Route/v1/data/research-paper-metrics

StatusLive

MIME typeapplication/json

Rate limit60/minute

Cache86400s public

dataresearchpaperscitationsopenalexbibliometricsdoiarxivinfluenceacademic

API URLhttps://x402.hexl.dev/v1/data/research-paper-metrics

Integration docs

Example request

{
  "id": "10.1126/science.1225829"
}

Example response

{
  "openAlexId": "https://openalex.org/W2045435533",
  "doi": "https://doi.org/10.1126/science.1225829",
  "title": "A Programmable Dual-RNA–Guided DNA Endonuclease in Adaptive Bacterial Immunity",
  "authors": [
    "Martin Jinek",
    "Krzysztof Chylinski",
    "Ines Fonfara",
    "Michael Hauer",
    "Jennifer A. Doudna",
    "Emmanuelle Charpentier"
  ],
  "authorCount": 6,
  "year": 2012,
  "venue": "Science",
  "type": "article",
  "metrics": {
    "citationCount": 17169,
    "citationsPerYear": 1226.4,
    "fwci": 191.466,
    "citationPercentile": 100,
    "topPercent": 1,
    "referencedWorksCount": 48
  },
  "openAccess": {
    "isOpenAccess": true,
    "status": "green",
    "url": "https://www.ncbi.nlm.nih.gov/pmc/articles/6286148"
  },
  "topConcepts": [
    {
      "name": "CRISPR and Genetic Engineering",
      "score": 0.999
    },
    {
      "name": "Bacterial Adaptive Immunity",
      "score": 0.991
    }
  ],
  "influence": {
    "label": "highly_cited",
    "reasons": [
      "citation percentile 100",
      "FWCI 191.466 (>=2x field average)"
    ]
  },
  "disclaimer": "Best-effort influence read derived from public OpenAlex metrics (FWCI, citation percentile, citation velocity). Citation data lags and varies by field/coverage; FWCI and percentile are absent for very recent or lightly-indexed works. NOT an authoritative bibliometric audit."
}

Input schema

{
  "type": "object",
  "required": [
    "id"
  ],
  "properties": {
    "id": {
      "type": "string",
      "description": "A DOI (10.x/...), arXiv id (e.g. 2005.14165), OpenAlex id (W…), or exact paper title."
    }
  },
  "examples": [
    {
      "id": "10.1126/science.1225829"
    },
    {
      "id": "2005.14165"
    },
    {
      "id": "Attention Is All You Need"
    }
  ]
}

Output schema

{
  "type": "object",
  "additionalProperties": true
}