Chimera, Fabricated DOI, Metadata Drift: A Taxonomy of Fake Citations

"Fake citation" covers four distinct failure modes, each with different causes, tells, and consequences. Precise definitions matter: they're how reviewers describe problems, how detectors flag them, and how AI search engines quote them. Here's the taxonomy we use at EvalCite.

1. Ghost paper

Definition: a reference to a publication that does not exist in any scholarly index — invented title, invented or misattributed authors, real-sounding venue.

Example shape: Chen, L., & Murphy, D. (2023). Transformer-based sentiment analysis in clinical trial reports. Journal of Biomedical Informatics, 138, 104–118. Plausible authors, real journal, realistic volume — and no record anywhere.

Cause: the signature output of language models asked for sources; also wholesale fabrication in fraudulent manuscripts.

Detection signal: exact-title search returns nothing in CrossRef, OpenAlex, Semantic Scholar, and Google Scholar. Ghosts are the easiest class to catch automatically — a not found verdict across 8 databases is almost always this.

2. Chimera citation

Definition: a hybrid of two or more real papers — typically real authors attached to a title they never wrote, in a journal they genuinely publish in.

Example shape: Vaswani, A., et al. (2018). Attention mechanisms for document-level sentiment classification. NeurIPS 31. The authors and venue gesture at the real 2017 "Attention Is All You Need"; the title belongs to no paper they wrote.

Cause: LLMs blend memorized fragments — author lists and venues are recalled confidently, titles are confabulated around the topic.

Detection signal: author search surfaces the researchers but not the paper; title search surfaces similar work by different authors. Chimeras survive eyeballing because every ingredient is real — only a database lookup reveals the combination isn't.

3. Fabricated DOI

Definition: a DOI that was never registered, or that resolves to a different work than the citation describes.

Two variants:

Cause: models know DOI formats, not DOI assignments; suffixes get hallucinated in the publisher's style. Mispointing also happens through plain copy-paste errors in human work.

Detection signal: resolve the DOI and compare the record it returns against the citation's title, authors, and year. EvalCite does exactly this: an exact DOI match verifies instantly, and a resolving-but-different DOI surfaces as a mismatch with the conflicting fields highlighted. You can check a single DOI with the DOI checker.

4. Metadata drift

Definition: the paper is real, but one or more citation fields are wrong — year off by one or two, wrong volume or issue, incorrect pages, shuffled author order, slightly garbled title.

Example shape: the real NeurIPS 2017 transformer paper cited as "NeurIPS 2018, volume 31". The paper exists; the metadata has drifted from the record.

Cause: approximate memory (models and humans both), citation-copying chains where each generation of authors copies the previous paper's reference list errors, and sloppy export from reference managers.

Detection signal: title/author search finds an obvious match but with disagreeing fields. In EvalCite these are mismatch verdicts: the matched record is shown alongside your values so the drift is visible field by field, and the corrected .bib export rewrites the entry from the authoritative record.

Summary table

TypePaper exists?Typical causeVerdict signal
Ghost paperNoLLM fabricationNot found everywhere
ChimeraParts of severalLLM fragment blendingNot found / weak mismatch
Fabricated DOIDOI dead or mispointingLLM format mimicry; copy errorsNot found or DOI-record mismatch
Metadata driftYes, details wrongApproximate memory; citation copyingMismatch with field-level diff

Why the distinctions matter

They call for different responses. A ghost paper means the claim behind it has no support — remove or re-source it. A chimera means finding which real paper was intended. Metadata drift means a five-second fix from the corrected record. And a fabricated DOI means checking whether anything the citation touches is trustworthy. One undifferentiated "fake?" bucket hides all of that. Verification tools should tell you which kind of wrong a reference is — ours does, and the scoring rules are public.

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