Development of a Sustainable Simulator and Simulation Program for Laparoscopic Skills Training in Haiti
Bibliographic record
Abstract
Laparoscopic surgery has been shown to have many favorable effects on surgical outcomes and postoperative recovery times. However, the cost of currently available training programs, such as the Fundamentals of Laparoscopic Surgery (FLS), limits their adoption in developing countries. To address this cost constraint, educators at the Justinian University Hospital (JUH) in Northern Haiti used local materials to build their own laparoscopic skills box trainer. This trainer is used to teach all surgical and OB/GYN residents in their laparoscopic skills program. The progressive curriculum consists of seven modules, three of which are for all trainees and four of which are specifically for surgery and OB/GYN (2). The seven modules are arranged in the order of difficulty; they start with basic maneuvers and progress to complex skills. This report describes both the preparation of the seven models and evaluation of the skills that are learned. This approach may facilitate global access to feasible, progressive, and sustainable laparoscopic training.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".