Extended score interval in the assessment of basic surgical skills
Bibliographic record
Abstract
INTRODUCTION: The Basic Surgical Skills course uses an assessment score interval of 0-3. An extended score interval, 1-6, was proposed by the Swedish steering committee of the course. The aim of this study was to analyze the trainee scores in the current 0-3 scored version compared to a proposed 1-6 scored version. METHODS: Sixteen participants, seven females and nine males, were evaluated in the current and proposed assessment forms by instructors, observers, and learners themselves during the first and second day. In each assessment form, 17 tasks were assessed. The inter-rater reliability between the current and the proposed score sheets were evaluated with intraclass correlation (ICC) with 95% confidence intervals (CI). RESULTS: The distribution of scores for 'knot tying' at the last time point and 'bowel anastomosis side to side' given by the instructors in the current assessment form showed that the highest score was given in 31 and 62%, respectively. No ceiling effects were found in the proposed assessment form. The overall ICC between the current and proposed score sheets after assessment by the instructors increased from 0.38 (95% CI 0.77-0.78) on Day 1 to 0.83 (95% CI 0.51-0.94) on Day 2. DISCUSSION: A clear ceiling effect of scores was demonstrated in the current assessment form, questioning its validity. The proposed score sheet provides more accurate scores and seems to be a better feedback instrument for learning technical surgical skills in the Basic Surgical Skills course.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".