The rate of publication of free papers at the 2008 and 2010 European Society of Sports Traumatology Knee Surgery and Arthroscopy congresses
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to evaluate the frequency with which free papers presented at the 2008 and 2010 European Society of Sports Traumatology Knee Surgery and Arthroscopy (ESSKA) congress were ultimately published in peer-reviewed journals. Moreover, this study evaluated whether any correlations exist between the level of evidence of the free papers and their frequency of publication or the impact factor of the journals in which they are published. METHODS: Free papers presented at the 2008 and 2010 ESSKA congresses were included for assessment. Clinical papers (observational studies and trials involving direct interaction between an investigator and human subjects) were graded for level of evidence by two independent reviewers. A comprehensive strategy was used to search the databases PubMed, Ovid (MEDLINE), and EMBASE for all publications corresponding to the included free papers. RESULTS: Three hundred-ninety presentations were evaluated, of which 215 (55%) were ultimately published in a peer-reviewed journal within five years of the presentation date. The mean time from presentation to publication was 16 months (SD 25 months). There was no significant difference in the distribution of the level of evidence between studies that were ultimately published, versus those that were not published (n.s.). The level of evidence of the published study was not a significant predictor of the impact factor of the journal in which it was published (n.s.). Presentations were most commonly published in Knee Surgery, Sports Traumatology, Arthroscopy (24%) and The American Journal of Sports Medicine (22%). CONCLUSION: Free papers at the 2008 and 2010 ESSKA congress were published at a frequency that is comparable to that at other orthopaedic meetings. The publication rate was similar across all levels of evidence. Further encouragement of manuscript preparation and submission following these meetings could help to ensure important research findings are disseminated to large audiences.
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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 | 0.122 | 0.406 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.048 | 0.036 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".