Bibliographic record
Abstract
OBJECTIVE: To provide incidence rates and days to symptom resolution and cognitive recovery stratified by sex and sport at a Canadian institution. STUDY DESIGN: A retrospective chart analysis. SUBJECTS: Seven hundred fifty-nine varsity level athletes competing in men's football, men's and women's soccer, men's and women's volleyball, men's and women's basketball, men's and women's ice hockey, women's field hockey, women's rugby, men's and women's tennis, men's and women's water polo, men's and women's swimming, badminton, cross-country, and track and field in the 2008 to 2009 season through the 2010 to 2011 season. MAIN OUTCOME MEASURES: Incidence of concussion, days to symptom recovery, and days to cognitive recovery as measured by clinical interpretation using the sports concussion assessment tool (SCAT)/SCAT2 and Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) with baseline and follow-up data. RESULTS: A total of 81 concussions were reported and diagnosed among 759 athletes. Significantly, more female athletes were concussed than male athletes (13.08%-7.53%, respectively; P = 0.014) with the highest rates in women's rugby [incidence density (ID) = 20.00 concussions per athlete-season], women's ice hockey (ID = 18.67 per athlete-season), and men's basketball (ID = 20.00 per athlete-season). Sex differences in symptom recovery and cognitive recovery were not significant. CONCLUSIONS: The incidence of concussion across multiple sports in a Canadian varsity athlete population is of concern. There are inconsistencies found between the time an athlete claims to have no symptoms and the time of neurocognitive recovery as measured by computerized neurocognitive testing. Therefore, objective computerized testing is recommended to ensure that athletes are functionally recovered before return to play.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".