999 Validation of Pediatric Cardiorespiratory Simulator: Simulresp
Bibliographic record
Abstract
Introduction To improve the training of medical students in respiratory physiology, we created an interactive cardio-respiratory simulator (SimulResp, figure 1). The objective of our study was to validate the simulator in normal and specific patient conditions. Methods We run SimulResp (version 2012.03.10.01) with several virtual patients characteristics: sex (M/F), age (8 to 18 years old) and weights (10 th, median, 90th percentiles), atmospheric pressure increase (simulation of scuba diving condition). SimulResp was run 3 times for each patient characteristic. We compared pH, PO2 and PCO2 obtained from the simulations to physiological values published in literature. Results Blood gases values obtained from SimulResp (figure 1) were within normal range (pH 7.35–7.45, PCO2 35–45 mmHg, PO2 80–100 mmHg). At 4.7 atmospheres, the difference with the published data (ref 1) was less than 10% for all values (figure 2). Conclusion The cardiorespiratory simulator, SimulResp, delivered blood gases values within normal range. The next step will be to implement clinical scenarios to facilitate medical student training. Reference (1) Cherry AD, Predictors of hypercapnia in immersed exercise at depth, JAP2008,106:316–325.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".