Comparative incidence of concussion and return to play time in two Canadian minor hockey groups over the 2011–2012 season
Bibliographic record
Abstract
Objective Report concussion incidence and Return to Play (RTP) times over a minor hockey season (2011–12) in two sub-groups, a community hockey association (A) and a private hockey academy (B). Design Retrospective, cohort study. Setting Elite hockey players from A and B. Subjects 354 subjects in two sub-groups. A: 222 (191 Males/31 Females). B: 132 (114 Males/18 Females). Intervention Subjects were educated and baseline tested at the start of the 2011–12 season using Symptom Inventory, SCAT2, BESS and neuro-cognitive testing. The Zurich 2008 RTP protocol was utilised. Subjects were followed with serial testing until recovered to baseline or within 5% of baseline. Medical authorisation was given to RTP. Outcome Measures The incidence of concussion and the average RTP in the two groups. Results A. Concussion incidence – Overall 23% ▸ A 18% (n=39) ▸ B 32% (n=42) B. RTP (Average No. Days to RTP) Overall: 22 ▸ A: 27 ▸ B: 14 Conclusions Concussion incidence approximated that reported by Echlin. The higher incidence in the B group reflects the experience of coaches and full-time athletic therapists in recognising and dealing with concussions, and a willingness to report concussion injury. Overall RTP time was longer in both groups than the previously reported 12.8 days average. For B, the RTP time was less than A (14 vs 27 days), reflecting daily access to supportive care (athletic therapists and physician), daily access to the gym for Steps 2 and 3, and daily ice-time for Steps 4 and 5 of the RTP protocol.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".