A Novel Mammoplasty Part-Task Trainer for Simulation of Breast Augmentation
Bibliographic record
Abstract
INTRODUCTION: Since the introduction of competency-based education and the restriction of residents' working hours, simulator-aided training has obtained increasing attention for its role in teaching and assessing resident surgical skills. Within plastic surgery training, such simulators would be particularly useful for aesthetic surgery procedures such as augmentation mammoplasty where residents have fewer opportunities for hands-on experience. The aims of this study were to develop a part-task trainer that allows plastic surgery trainees to acquire skills necessary for augmentation mammoplasty and to assess its potential value as a training tool. METHODS: The mammoplasty part-task trainer (MPT) was designed to have a reusable and rigid thorax base and "soft" disposable layers to mimic the skin and subcutaneous tissues. A mock unilateral subglandular breast augmentation was performed by 4 board-certified plastic surgeons using standard instruments and scored using a 0 to 5 Likert scale where a score of 5 was considered the most satisfactory. RESULTS: Four board-certified plastic surgeons participated in the survey. On a scale of 0 to 5, the MPT's "value" as a training tool, "relevance to practice," and "physical attributes" scored highest, with mean values of 4.5, 4.3, and 4.1, respectively. "Realism of experience," "ability to perform tasks," and "realism of material" scored 3.9, 3.8, and 3.7, respectively. The observed average of the "global assessment" of the MPT was 4.3. The cost of fabrication of the MPT was estimated at approximately Can $113. CONCLUSIONS: This study describes a preliminary novel mammoplasty task trainer that was highly valued by experts as a potential training tool.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 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".