Accelerated publication versus usual publication in 2 leading medical journals.
Bibliographic record
Abstract
BACKGROUND: A number of medical journals have developed policies for accelerated publication of articles judged by the authors, the editors or the peer reviewers to be of special importance. However, the validity of these judgements is unknown. We therefore compared the importance of articles published on a "fast track" with those published in the usual way. METHODS: We identified 12 "case" articles--6 articles from the New England Journal of Medicine that were prereleased on the journal's Web site before publication in print and 6 "fast-tracked" articles from The Lancet. We then identified 12 "control" articles matched to the case articles according to journal, disease or procedure of focus, theme area and year of publication. Forty-two general internists rated the articles, using 10-point scales, on dimensions addressing the articles' importance, ease of applicability and impact on health outcomes. RESULTS: For each dimension, the mean score for the case articles was significantly higher than the mean score for the control articles: importance to clinical practice 7.6 v. 7.1 respectively (p = 0.001), importance from a public health perspective 6.5 v. 6.0 (p < 0.001), contribution to advancement of medical knowledge 6.2 v. 5.8 (p < 0.001), ease of applicability in practice 7.0 v. 6.5 (p < 0.001), potential impact on health outcomes 6.5 v. 5.9 (p < 0.001). Despite these general findings, in 5 of the 12 matched pairs of articles the control article had a higher mean score than the case article across all the dimensions. INTERPRETATION: The accelerated publication practices of 2 leading medical journals targeted articles that, on average, had slightly higher importance scores than similar articles published in the usual way. However, our finding of higher importance scores for control articles in 5 of the 12 matched pairs shows that current journal practices for selecting articles for expedited publication are inconsistent.
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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 | 0.097 | 0.393 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.024 | 0.021 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".