The Ottawa Surgical Competency Operating Room Evaluation (O-SCORE)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 it