Validation of novel and objective measures of microsurgical skill: Hand‐motion analysis and stereoscopic visual acuity
Bibliographic record
Abstract
Our purposes were: 1) to establish the predictive validity of stereoscopic visual acuity and microsurgical performance, and 2) to establish the construct and concurrent validity of hand-motion analysis as an objective and sensitive measure of microsurgical performance. Using a surgical microscope, 50 surgical residents completed a standardized microsurgical suturing task at baseline and following microsurgical training. Microsurgical performance was evaluated by blinded, expert microsurgeons using global rating scales. Measures of stereoscopic visual acuity and hand-motion analysis were correlated with expert global rating scores. Global rating scores correlated significantly with number of hand movements (r = -0.47, P = 0.001) and hand-travel distance (r = -0.37, P = 0.008). Economy of hand-motion improved significantly following microsurgical training (number of hand movements, P = 0.046; hand-travel distance, P = 0.04). Measures of stereoscopic visual acuity did not correlate significantly with global rating scores. Hand-motion analysis appears to be an objective and sensitive instrument for assessing microsurgical performance, with evidence of both concurrent and construct validity. The predictive validity of stereoscopic visual acuity and microsurgical performance remains unclear.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".