Simulation in paediatrics: An educational revolution
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recent changes in the culture of medical education have highlighted deficiencies in the traditional apprenticeship model of education, and emphasized the need for more experiential modalities of learning. Simulations, which are scenarios or environments designed to closely approximate real-world situations, have recently found their way into the medical training of health care providers. High-fidelity simulators are life-like mannequins connected to computer systems that control the physiological and physical responses of the mannequin. These simulators are able to provide direct feedback to learners in safe, risk-free environments. This technology has been used to teach all aspects of medical care, including medical knowledge, technical skills, and behavioural training or communication skills. The present article provides a general overview of simulation that will hopefully help to generate interest in paediatric simulation across Canada. Several tertiary care paediatric hospitals in Canada are already using simulation to teach health care providers; continued growth and interest is expected in this exciting area of medical education.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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 it