Author self-citation in the diabetes literature
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Author self-citation is the practice of citing one's previous publications in a new publication. Its extent is unknown. We studied author self-citation, choosing the major clinical field of diabetes mellitus to represent the general medical literature. METHODS: We identified every article about diabetes mellitus in 170 hand-searched clinical journals published in 2000. For every article, we recorded the bibliographic citation and publication type (original or review article) and assessed the methodologic rigour. Citation information was obtained from the ISI Web of Knowledge in April 2003. RESULTS: Of 49,028 articles, 289 were about diabetes mellitus and had citation information. Citation counts ranged from 0 to 347 (median 6, interquartile range [IQR] 2-12). Author self-citation counts ranged from 0 to 16 (median 1, IQR 0-2). Author self-citations accounted for an average of 18% (95% confidence interval [CI] 15%-21%) and a median of 7% (95% CI 5%- 11%) of all citations of each publication that was cited at least once (n = 266). Original articles had double the mean proportion of author self-citations compared with review articles (19% v. 9%; median 7% v. 0%, difference 7%, 95% CI 0- 10%). Methodologic rigour and review type were not significantly associated with subsequent author self-citation. INTERPRETATION: Nearly one-fifth of all citations to articles about diabetes mellitus in clinical journals in the year 2000 were author self-citations. The frequency of self-citation was not associated with the quality of publications. These findings are likely applicable to the general clinical medicine literature and may have important implications for the assessment of journal or publication importance and the process of scientific discovery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it