Development and Initial Assessment of a Novel and Customized Bile Duct Simulator for Handsewn Anastomosis Training
Bibliographic record
Abstract
Simulation-based medical education allows for the training and maintenance of healthcare skills in a safe and controlled environment. In this technical report, the development and initial evaluation of a bile duct anastomosis simulator are described. The simulator was developed using additive manufacturing techniques such as three-dimensional (3D) printing and silicone work. The final product was produced by maxSIMhealth, a research lab at Ontario Tech University (Oshawa, ON, Canada), and included four individual silicone bile ducts, based on the expert opinions from surgeons at the Centre Hospitalier de l'Université de Montréal (Montreal, QC, Canada), and a 3D-printed maxSIMclamp, which was described in a previous report. The evaluation was conducted by nine individuals consisting of surgeons, surgical residents, and medical students to assess the fidelity, functionality, and teaching quality of the simulator. The results from the evaluation indicate that the simulator needs to improve its fidelity by being softer, thinner, and beige. On the other hand, the results also indicate that this simulator is extremely durable and can be used as a training tool for surgical residents with some minor improvements.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".