An evidence‐based medicine fellowship in a children’s teaching hospital
Bibliographic record
Abstract
This paper reports the introduction of an evidence-based medicine fellowship in a children's teaching hospital. The results are presented of a self-reported 'evidence-based medicine' questionnaire, the clinical questions requested through the information retrieval service are outlined and the results of an information retrieval service user questionnaire are reported. It was confirmed that clinicians have frequent clinical questions that mostly remain unanswered. The responses to four questions with 'good quality' evidence-based answers were reviewed and suggest that at least one-quarter of doctors were not aware of the current best available evidence. There was a high level of satisfaction with the information retrieval service; 19% of users indicated that the information changed their clinical practice and 73% indicated that the information confirmed their clinical practice. The introduction of an evidence-based medicine fellowship is one method of disseminating the practice of evidence-based medicine in a tertiary children's hospital.
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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 | 0.020 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".