A national network for the tele-education of canadian residents in pediatric cardiology
Bibliographic record
Abstract
A trial of 11 video-conferenced teaching sessions for residents in pediatric cardiology was performed by the 7 training programs in Canada in order to share expertise in specialized areas, to expose trainees to educational telemedicine, and to acquaint residents with other programs and personnel. Topics included cardiac pathology, arrhythmias, magnetic resonance imaging, fetal physiology, pulmonary hypertension, and cardiomyopathy. The sessions were evaluated by 93 residents by questionnaire for content and technology. Session content was highly rated. Videoconference picture quality was highly rated, but sound quality and visual aids were rated as neutral or unsatisfactory by a significant minority, related to problems with several early sessions, subsequently corrected. 60% of respondents rated the videoconferences as good as live presentations. Presenters were generally satisfied although they required some adjustments to videoconferencing. The average cost per session was $700 Canadian. Videoconferencing of resident educational sessions was generally well accepted by most presenters and residents, and the trial has formed the basis for a national network. Adequate organizational time, and careful attention to audiovisual needs, are most important. Videoconference guidelines are suggested for presenters based on this experience.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 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".