Bibliometric Analysis of Neurology Articles Published in General Medicine Journals
Bibliographic record
Abstract
Importance: A significant portion of neurology literature is published in general medicine journals. Despite this, a detailed examination of publication patterns of neurology articles in these journals has not yet been carried out. Objective: To examine the publication patterns of neurology articles in general medicine journals during a 10-year period using a bibliometric approach. Design, Setting, and Participants: This cross-sectional bibliometric analysis identified the top 5 general medicine journals using the 2017 Journal Citations Report. Four other medical subspecialties (ie, immunology, endocrinology, gastroenterology, and pulmonology) were selected for comparison of publication patterns with neurology. Using MEDLINE, the 5 journals were searched for articles published between 2009 and 2018 that were indexed with the following MeSH terms: nervous system diseases, immune system diseases, endocrine system diseases, gastrointestinal diseases, and respiratory tract diseases. Data analysis was conducted from February 2019 to December 2020. Main Outcomes and Measures: Publications were characterized by journal, specialty, and study design. These variables were used for comparison of publication numbers. Results: The general medicine journals with the 5 highest journal impact factors (JIF) were New England Journal of Medicine (NEJM; JIF 79.3), Lancet (JIF 53.3), JAMA (JIF 47.7), BMJ (JIF 23.6), and PLOS Medicine (JIF 11.7). Our bibliometric search yielded 3719 publications, of which 1098 (29.5%) were in neurology. Of these 1098 neurology publications, 317 (28.9%) were published in NEJM, 205 (18.7%) in Lancet, 284 (25.9%) in JAMA, 214 (19.5%) in BMJ, and 78 (7.1%) in PLOS Medicine. Randomized clinical trials were the most frequent neurology study type in general medicine journals (519 [47.3%]). The number of publications in each of the other specialties were as follows: immunology, 817; endocrinology, 633; gastroenterology, 353; and pulmonology, 818. Conclusions and Relevance: The results of this study provide some guidance to authors regarding where they may wish to consider submitting their neurology research. Compared with other specialties, neurology-based articles are published more frequently in general medicine journals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.118 | 0.154 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".