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Academic Evidence Pack — Citation Integrity Report
x402
Academic Evidence Pack — Citation Integrity Report is a paid API for AI agents from aep-api.fly.dev, paid per call via x402, $1/call, status unknown (last checked 2026-09-15).
Verifies up to 50 bibliography references for existence, resolution, retraction/correction status, title/author/year match accuracy, and fabrication risk, returning a cryptographically signed (Ed25519, RFC 8785) byte-reproducible JSON report.
Price / call$1
Success—
StatusUnknown
How this service works
Verify a bibliography. For every reference: exists, resolves, retracted/corrected/flagged, title/author/year match against the registered record, and a rule-derived fabrication risk — as a signed (Ed25519, RFC 8785 canonical JSON), byte-reproducible JSON report. Input: structured references or BibTeX. No LLM; every claim carries its source and retrieval time. Tier: standard, up to 50 references.
Output
A signed (Ed25519, RFC 8785 canonical JSON) byte-reproducible JSON report containing: per-reference verdicts (verified, not_found, unresolvable), existence and resolution checks, integrity flags (retraction, correction, expression of concern), title similarity scores, author match results, fabrication risk labels (low/medium/high/n_a), resolved metadata (DOI, title, venue, authors, OpenAlex ID), provenance with retrieval timestamps, and a summary with aggregate stats. Also includes cache/latency/upstream call statistics and a warnings array for interpretive caveats.
Example use cases
Pre-submission bibliography audit
“I'm about to submit my dissertation and want to make sure all 40 citations are real, resolve correctly, and haven't been retracted. Here's the BibTeX file — can you run a full citation integrity check and tell me which ones are flagged or at high fabrication risk?”
Detecting hallucinated AI-generated citations
“I used an AI assistant to draft a literature review and I'm worried some of the references it invented might not be real. Can you check these 20 structured references — DOIs, titles, and authors included — and tell me which ones don't exist or have mismatched metadata?”
Retraction screening before evidence synthesis
“I'm doing a systematic review and need to make sure none of the 35 studies in my final list have been retracted or corrected since publication. Please verify this BibTeX bibliography and flag any integrity issues, including post-publication updates.”
Technical details
Endpoint
POSThttps://aep-api.fly.dev/v1/citation-reportWhen to prefer
Choose this endpoint when you need a non-LLM, source-attributed, cryptographically verifiable citation integrity report — especially when the output must be auditable, reproducible, or attached as evidence to a submission. Prefer it over general web search or LLM-based fact-checking when retraction status, author-metadata matching, and fabrication risk scoring with provenance timestamps are required. It is particularly valuable for screening AI-generated bibliographies, pre-submission manuscript audits, and systematic review pipelines where integrity certification matters.
Side effects
- References exceed 50-item limit for standard tier — server rejects or truncates
- DOI not registered at Crossref or indexed by OpenAlex — reference marked 'not_found'
- Upstream API (Crossref/OpenAlex) timeout or outage — resolution result may be incomplete
- BibTeX parse error due to malformed syntax — server may reject the request
- Ambiguous free-text raw citation with no DOI or title — low match confidence, may return 'unresolvable'
- Payment failure or insufficient USDC balance — 402 response, report not generated
- Title similarity below match threshold — verdict 'verified_with_discrepancies' or 'not_found' even if DOI resolves
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bibtex | string | A BibTeX bibliography; parsed server-side (entry key → reference id). Bounded at 262144 UTF-8 bytes (the parser's unit); maxLength counts characters and is exact for ASCII. |
| options | object | |
| references | array |
Output
Schema · Response
{
"type": "json",
"example": {
"stats": {
"cache": "miss",
"latency_ms": 1800,
"upstream_calls": {
"crossref": 2,
"openalex": 2,
"unpaywall": 0
}
},
"report": {
"tier": "standard",
"issuer": {
"kid": "…",
"name": "Academic Evidence Pack — Citation Integrity Report"
},
"version": "1",
"issued_at": "2026-09-02T12:00:00.000Z",
"price_usd": "1.00",
"input_hash": "sha256:…",
"reference_count": 2,
"ruleset_version": "2026-09-02.5"
},
"summary": {
"verified": 1,
"not_found": 1,
"unresolvable": 0,
"fabrication_risk": {
"low": 1,
"n_a": 0,
"high": 1,
"medium": 0
},
"integrity_flagged": 1,
"verified_with_discrepancies": 0
},
"warnings": [
"fabrication_risk is a rule-derived label (see report.ruleset_version), not a probability. …"
],
"signature": {
"alg": "EdDSA",
"jws": "eyJ…..…",
"kid": "…",
"payload_hash": "sha256:…",
"canonicalization": "RFC 8785 JCS"
},
"references": [
{
"id": "wolfe2011",
"input": {
"id": "wolfe2011",
"doi": "10.1126/science.1197258",
"year": 2011,
"title": "…",
"authors": [
"Felisa Wolfe-Simon"
]
},
"checks": {
"match": {
"method": "doi",
"year_delta": 0,
"title_similarity": 1000,
"venue_similarity": null,
"all_authors_match": null,
"author_list_prefix": true,
"first_author_match": true,
"candidates_considered": 0
},
"exists": "true",
"resolves": {
"result": "true",
"definition": "registered at Crossref or indexed by OpenAlex"
},
"integrity": {
"note": "Post-publication update record(s) found. Review before citing.",
"status": "known",
"updates": [
{
"doi": "10.1126/science.adu5488",
"date": "2025-07-24T00:00:00Z",
"type": "retraction",
"source": "crossref"
}
],
"sources_checked": [
"openalex",
"crossref"
]
},
"doi_syntax": "true"
},
"reasons": [],
"verdict": "verified",
"resolved": {
"doi": "10.1126/science.1197258",
"type": "article",
"year": 2011,
"title": "…",
"venue": "Science",
"authors": [
{
"name": "Felisa Wolfe-Simon",
"orcid": null
}
],
"openalex": "W2135819747",
"source_urls": [
"https://doi.org/10.1126/science.1197258",
"https://openalex.org/W2135819747"
]
},
"provenance": {
"title": {
"source": "openalex",
"retrieved_at": "…"
},
"integrity": {
"source": "crossref",
"retrieved_at": "…"
}
},
"fabrication_risk": "low",
"integrity_flagged": true
},
{
"id": "lee2022",
"input": {
"id": "lee2022",
"year": 2022,
"title": "…",
"venue": "CVPR",
"authors": [
"Min-Jun Lee",
"Soo-Young Kim"
]
},
"checks": {
"match": {
"method": null,
"year_delta": null,
"title_similarity": null,
"venue_similarity": null,
"all_authors_match": null,
"author_list_prefix": null,
"first_author_match": null,
"candidates_considered": 3
},
"exists": "n_a",
"resolves": {
"result": "n_a",
"definition": "registered at Crossref or indexed by OpenAlex"
},
"integrity": {
"note": "No registered record to check.",
"status": "n_a",
"updates": [],
"sources_checked": []
},
"doi_syntax": "n_a"
},
"reasons": [
"no_matching_record"
],
"verdict": "not_found",
"resolved": null,
"provenance": {},
"fabrication_risk": "high",
"integrity_flagged": false
}
],
"partial_failures": []
}
}Tags
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