Concussions During the 1997 Canadian Football League Season
Bibliographic record
Abstract
OBJECTIVE: To examine the incidence and characteristics of concussions for one season in the Canadian Football League (CFL). DESIGN: Retrospective survey. PARTICIPANTS: 289 players reporting to CFL training camp. Of these, 154 players had played in the CFL during the 1997 season. MAIN OUTCOME MEASURES: Based on self-reported symptoms, calculations were made to determine the number of concussions experienced during the previous season, the duration of symptoms, the time for return to play after concussion, and any associated risk factors for concussions. RESULTS: Of all the athletes who played during the 1997 season, 44.8% experienced symptoms of a concussion. Only 18.8% of these concussed players recognized they had suffered a concussion. 69.6% of all concussed players experienced more than one episode. Symptoms lasted at least 1 day in 25.8% of cases. The odds of experiencing a concussion increased 13% with each game played. A past history of a loss of consciousness while playing football and a recognized concussion while playing football were both associated with increased odds of experiencing a concussion during the 1997 season. CONCLUSION: Many players experienced a concussion during the 1997 CFL season, but the majority of these players may not have recognized that fact. Players need to be better informed about the symptoms and effects of concussions.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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".