The Fundamentals of Laparoscopic Surgery and LapVR evaluation metrics may not correlate with operative performance in a novice cohort
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
BACKGROUND: Considerable resources have been invested in both low- and high-fidelity simulators in surgical training. The purpose of this study was to investigate if the Fundamentals of Laparoscopic Surgery (FLS, low-fidelity box trainer) and LapVR (high-fidelity virtual reality) training systems correlate with operative performance on the Global Operative Assessment of Laparoscopic Skills (GOALS) global rating scale using a porcine cholecystectomy model in a novice surgical group with minimal laparoscopic experience. METHODS: Fourteen postgraduate year 1 surgical residents with minimal laparoscopic experience performed tasks from the FLS program and the LapVR simulator as well as a live porcine laparoscopic cholecystectomy. Performance was evaluated using standardized FLS metrics, automatic computer evaluations, and a validated global rating scale. RESULTS: Overall, FLS score did not show an association with GOALS global rating scale score on the porcine cholecystectomy. None of the five LapVR task scores were significantly associated with GOALS score on the porcine cholecystectomy. CONCLUSIONS: Neither the low-fidelity box trainer or the high-fidelity virtual simulator demonstrated significant correlation with GOALS operative scores. These findings offer caution against the use of these modalities for brief assessments of novice surgical trainees, especially for predictive or selection purposes.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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