Une version québécoise du Sport Concussion Assessment Tool 2 (SCAT2)—Outil d'évaluation des commotions cérébrales dans le sport 2 : Québec (SCAT2-Qc)
Bibliographic record
Abstract
OBJECTIVE: To translate the Sport Concussion Assessment Tool 2 (SCAT2) based on the French spoken in Quebec and to confirm its acceptability for Quebec's francophone population. METHODOLOGY: The original SCAT2 was translated using a modified approach of the tool translation and adaptation method as proposed by the World Health Organization. A parallel translation was done first. A review of that translation by a committee then led to a preliminary SCAT2-Qc version. A parallel back-translation was then done and compared to the original version. The preliminary version was subsequently modified. The final version was then obtained through comments and suggestions during testing of the tool on two healthy subjects and from the comparison of the SCAT2-Qc with the existing French version by three reviewers from the health field. The final version of the SCAT2-Qc was eventually tested on 12 healthy subjects to ensure its acceptability. RESULTS: The 12 healthy subjects did not experience any comprehension difficulties when using the SCAT2-Qc. CONCLUSION: The translation steps undertaken made it possible to create the SCAT2-Qc that can now be validly used in the Quebec sport and scientific community.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".