Bridging the Evidence-to-Practice Gap at Scale: Evolving Evidence2Practice Ontario by Using the Pan-Canadian HALO Framework
Bibliographic record
Abstract
Clinical decision support tools such as Evidence2Practice Ontario (E2P) can be an effective way to reduce the 17-year gap between clinical innovation and its use in practice. To enhance the interoperability and scalability of E2P we propose leveraging the pan-Canadian Health Application Lightweight Protocol (HALO) framework. Public and private developers could be informed by E2P as the initial use case to test the capability of HALO to support clinical decision support tools.
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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 | 0.181 | 0.312 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.017 | 0.020 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.022 | 0.015 |
| Open science | 0.009 | 0.027 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".