Rationale, development and implementation of the ReACanROC registry for out-of-hospital cardiac arrests in France and Canada
Bibliographic record
Abstract
France and Canada prehospital systems and care delivery in out-of-hospital cardiac arrests (OHCAs) show substantial differences. This article aims to describe the rationale, design, implementation and expected research implications of the international, population-based, France-Canada registry for OHCAs, namely ReACanROC, which is built from the merging of two nation-wide, population-based, Utstein-style prospectively implemented registries for OHCAs attended to by emergency medical services. Under the supervision of an international steering committee and research network, the ReACanROC dataset will be used to run in-depth analyses on the differences in organisational, practical and geographic predictors of survival after OHCA between France and Canada. ReACanROC is the first Europe-North America registry ever created to meet this goal. To date, it covers close to 80 million people over the two countries, and includes approximately 200 000 cases over a 10-year period.
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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 | 0.114 | 0.110 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".