The Fate of Manuscripts Rejected by The Journal of Bone and Joint Surgery (American Volume)
Bibliographic record
Abstract
BACKGROUND: Of the many manuscripts that are submitted to The Journal of Bone and Joint Surgery (American Volume) (JBJS-A) for publication, the majority are not accepted. However, little is known about the outcome of these rejected submissions. To determine the fate of studies rejected by JBJS-A, we conducted a follow-up investigation of all clinical and basic science manuscripts that were submitted to The Journal between January 2004 and June 2005 but were not accepted. METHODS: For each rejected manuscript, data were extracted on a wide variety of scientific and nonscientific characteristics, which were plausibly related to subsequent publication. PubMed searches were conducted to determine which manuscripts achieved full publication within five years, and logistic regression was used to identify the factors associated with publication. To further elucidate the factors associated with publication, a survey was administered to the corresponding author of each rejected manuscript. RESULTS: At five years following rejection by JBJS-A, 75.8% (696 of 918) of manuscripts had reached full publication. In the multivariate analysis, factors associated with a higher likelihood of subsequent publication included grade of initial review by JBJS-A (p = 0.029), disclosure of a for-profit or nonprofit conflict of interest (p = 0.028 and 0.027, respectively), and a greater number of prior publications in frequently cited orthopaedic journals by the corresponding author (p < 0.0001). Manuscripts were less likely to reach full publication if the corresponding author was from Asia or the Middle East (p = 0.004) or was a woman (p = 0.003). Among survey respondents who indicated that their study had not yet reached full publication, the most commonly cited reason was lack of time (reported by 51.4% of respondents [thirty-eight of seventy-four]). CONCLUSIONS: Most manuscripts (75.8%) not accepted by JBJS-A were published elsewhere within five years of rejection. The factors predictive of subsequent publication were primarily investigator-related as opposed to study-related. Given this low threshold for eventual publication, readers are encouraged to use criteria other than inclusion in the PubMed database to identify high-quality papers.
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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 | 0.100 | 0.440 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".