Strengthening health systems through networks: the need for measurement and feedback
Bibliographic record
Abstract
Centre for Clinical Epidemiology and Evaluation, University of British Columbia, Vancouver, BC, Canada, School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada, School of Population Health and Clinical Practice, University of Adelaide, Adelaide, SA, Australia, Propel Centre for Population Health Impact, The University of Waterloo, Waterloo, ON, Canada, InSource Research Group, Vancouver, BC, Canada and Centre for the Development of Best Practices in Health, Yaounde Central Hospital, Cameroon *Corresponding author. NHMRC Sidney Sax Fellow, Centre for Clinical Epidemiology and Evaluation, VCH Research Institute j The University of British Columbia, Research Pavilion, 7th Floor, 828 West 10th Avenue, Vancouver, BC V5Z 1M9, Canada. E-mail: Cameron.willis@ubc.ca
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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 | 0.013 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 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 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".