Designing and Implementing a Comprehensive Simulation Curriculum in Internal Medicine Residency
Bibliographic record
Abstract
Medical simulation is the use of a device or series of devices to emulate anatomy, real-life clinical situations, and clinical procedures for the purposes of education, evaluation, and research. 1 , 2 Simulation is a powerful tool in the education and evaluation of physicians and is rapidly becoming a central thread in the fabric of medical education. 3 The effectiveness of simulation-based medical education (SBME) can be optimized by integrating simulation into an overall curriculum. 4 Internal medicine training programs are introducing procedural training using simulation but are not as advanced as other programs, such as anesthesia and emergency medicine, in the use of technology-based simulation utilizing high-fidelity full-size mannequins. 5 We feel simulation can be used to teach a wide range of CanMEDS competencies, and a comprehensive simulation curriculum should become a standard in internal medicine residency training.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".