An observational study of duplicate presentation rates between two national orthopedic meetings.
Bibliographic record
Abstract
BACKGROUND: National meetings such as those of the American Academy of Orthopaedic Surgeons (AAOS) and the Canadian Orthopaedic Association (COA) are invaluable in the dissemination of new research findings. Given the limits of meeting agendas, investigators who present the same paper at multiple meetings prevent other presentations on potentially important original research. To determine the incidence of duplicate presentation of research between recent COA and AAOS meetings and between national meetings (AAOS and subspecialty), we conducted an observational study. METHODS: We hand-searched all podium papers and posters from the 2001 COA annual meeting for duplicate presentation at the 2001 and 2002 AAOS annual meetings and subspecialty meetings held in the USA. We evaluated summary data abstracted from the duplicate presentations for consistency. RESULTS: Of 148 presentations at the 2001 COA meeting, 29 presentations (paper and poster) were duplicated at the 2001 or 2002 AAOS meeting: effectively 1 paper in 5 (19.5%). Canadian investigators were significantly more likely to present the same paper at both meetings than Americans (79% v. 13%, respectively; p < 0.01). Those who presented papers at COA altered their AAOS presentations in a variety of ways: by changing the wording in the title of their paper (24% of the time), adding or removing authors (38%), changing authorship order (34%) and changing the sample size (31%). Duplicate presentation rates between AAOS and other orthopedic subspecialty meetings averaged 11.4% (range 3.4%-26.4%). CONCLUSIONS: We identified a 20% duplicate presentation rate between the COA and AAOS annual meetings, and an 11% rate between the AAOS and subspecialty meetings. Stricter enforcement of guidelines and improved dissemination of research findings at both national meetings may limit this practice.
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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 | 0.043 | 0.269 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".