Global retractions due to randomly generated content: Characterization and trends
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Randomly generated content has emerged as a major driver of retractions: in 2024 alone, over 2300 such cases were recorded, far exceeding three cases in 2010.
“More concerningly, randomly generated content has emerged as a major driver of retractions: in 2024 alone, over 2300 such cases were recorded-far exceeding the mere three cases documented in 2010 (Lei et al., 2024).”
From The Attention Mismatch: Mapping the Structural Academic Governance Deficit in the Age of Generative AI (2026) · cites this paper as Lei et al., 2024
The citation lists haven’t been fetched yet
References 33 · Cited by 35
- Authors
- Lei, F., Du, L., Dong, M., & Liu, X.
- Affiliations
- Sichuan University (CN)
- Corresponding author
- Liu, Xuemei
- Venue
- Scientometrics
- Published
- 2024-10-03
- Volume
- 129
- Issue
- 12
- Pages
- 7943-7958
- ISSN
- 0138-9130 (ISSN-L)
- 1588-2861
- OpenAlex
- W4403096437
- Cited by
- 35
- References
- 33
- Citations by year
- 2026: 21 · 2025: 14
- FWCI
- 11.28
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Scientometrics (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Social Sciences › Decision Sciences › Information Systems and Management › Academic Publishing and Open Access
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
- Keywords
- retracted article, AI-generated text, research integrity, open access journals, journal closure, Retraction Watch
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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