Recommendations for policy development regarding sport-related concussion prevention and management in Canada
Bibliographic record
Abstract
The Canadian Concussion Collaborative (CCC) is composed of health-related organisations concerned with the recognition, treatment and management of concussion. Its mission is to create synergy between organisations concerned with concussion to improve education and implementation of best practices for the prevention and management of concussions. Each of the organisations that constitute the CCC has endorsed two recommendations that address the need for relevant authorities to develop policies about concussion management in sports. The recommendations were developed to support advocacy for regulations, policies or legislation to improve concussion prevention and management at all levels of sport.
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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 | 0.089 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.009 | 0.005 |
| Research integrity | 0.023 | 0.012 |
| Insufficient payload (model declined to judge) | 0.029 | 0.003 |
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".