Emergency Department Presentation of a Patient with a Severe Upper Gastrointestinal Bleed: A Simulation Case for Training Emergency Medicine Residents
Bibliographic record
Abstract
Emergency medicine practitioners frequently encounter acute presentations requiring quick, directed treatment to ensure the best patient outcome. Training residents in the appropriate clinical and procedural skills often proves difficult when treating the patient who is critically unwell. Simulation-based medical education is an effective modality that enables teaching around life-threatening medical conditions in a safe space for learners while avoiding adverse complications for patients. Severe gastrointestinal bleeding is one such condition that emergency medicine practitioners would benefit from encountering first in a simulation environment due to its high rate of morbidity and mortality if not quickly managed appropriately. This report describes a simulated scenario of an undifferentiated patient who is acutely unwell and then becomes hemodynamically unstable secondary to a severe gastrointestinal bleed. Delivery of the case is facilitated by the detailed technical report herein. It contains a stepwise, detailed summary of appropriate learners' actions and suggestions for learning objectives relating to the case.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| 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".