The Ottawa Surgical Competency Operating Room Evaluation (O-SCORE)
Bibliographic record
Abstract
PURPOSE: Most assessment of surgical trainees is based on measures of knowledge, with limited evaluation of their competence to actually perform various surgical procedures. In this study, the authors evaluated a tool they designed to assess a trainee's competence to perform an entire surgical procedure independently, regardless of procedure type or postgraduate year (PGY). METHOD: In phase 1, the Ottawa Surgical Competency Operating Room Evaluation (O-SCORE) was piloted in the University of Ottawa's Division of Orthopaedic Surgery. In phase 2, the refined 11-item tool (8 items rated on a 5-point competency scale, 1 item assessing procedural competence, 2 feedback items) was used in the Divisions of Orthopaedic Surgery and General Surgery to assess residents' performance on 11 common procedures. Quantitative and qualitative analyses were conducted. RESULTS: In phase 2, 34 orthopaedic and general surgeons assessed the performance of 37 residents in 163 procedures. ANOVA demonstrated an effect of PGY. Post hoc analysis found that total procedure scores for PGYs 1 and 2 were lower than those for PGY 3 (P<.001), and PGY 3 scores were lower than those for PGYs 4 and 5 (P<.02). Analysis of qualitative data indicated that the rating scale was practical and useful for surgeons and residents. CONCLUSIONS: This novel evaluation tool successfully discriminated between junior and senior residents and identified surgical competency across various PGY levels regardless of procedure type. Multiple sources of evidence support the O-SCORE as a valid tool for the assessment of trainee operative competency.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".