Acquisition and evaluation of surgical skills using a laparoscopic physical simulator
Bibliographic record
Abstract
A physical surgical simulator, the McGill Inanimate System for Training and Evaluation of Laparoscopic Skills (MISTELS) is used to examine the acquisition of laparoscopic skills, as well as to determine a summative evaluation of these skills. The cumulative summation method (CUSUM) is used to characterize individual and group learning curves for a MISTELS task. To examine transfer of learning in laparoscopy, novice laparoscopists were randomized to either practice a basic psychomotor task (peg board transfer) or to a no-practice control group. After forty iterations, the novices performed a more complex task (suturing); those who practiced the basic task significantly improved their complex task performance. Finally, using the receiver operator curve (ROC), the summative evaluation score for MISTELS was determined by maximizing the sensitivity and specificity of this training instrument. Using these findings, individualized training programs can be developed to teach essential laparoscopic skills prior to entering the operating room.
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.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".