Development of the Champlain primary care cardiovascular disease prevention and management guideline
Bibliographic record
Abstract
Problem addressed A well documented gap remains between evidence and practice for clinical practice guidelines in cardiovascular disease (CVD) care. Objective of program As part of the Champlain CVD Prevention Strategy, practitioners in the Champlain District of Ontario launched a large quality-improvement initiative that focused on increasing the uptake in primary care practice settings of clinical guidelines for heart disease, stroke, diabetes, and CVD risk factors. Program description The Champlain Primary Care CVD Prevention and Management Guideline is a desktop resource for primary care clinicians working in the Champlain District. The guideline was developed by more than 45 local experts to summarize the latest evidence-based strategies for CVD prevention and management, as well as to increase awareness of local community-based programs and services. Conclusion Evidence suggests that tailored strategies are important when implementing specific practice guidelines. This article describes the process of creating an integrated clinical guideline for improvement in the delivery of cardiovascular care.
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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 | 0.027 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".