Frequency and Magnitude of Head Accelerations in a Canadian Interuniversity Sport Football Team’s Training Camp and Season
Bibliographic record
Abstract
The increased awareness of concussion in sport has led to an examination of head impacts and the associated biomechanics that occur during these sporting events. The high rate of concussions in football makes it particularly relevant.1 The purpose of this study was to examine how frequently, and to what magnitude, Canadian University football players get hit in training camp and how this compares to practices and games in regular season. An ANOVA with repeated measures indicated that, on average, players were hit significantly more in games (45.2 hits) than training camp sessions (17.7 hits) and practices (8.0 hits), while training camp was associated with significantly more hits than practices (p < .001, η2 = .392). Multiple positional differences were found. In particular, significantly more hits were experienced by offensive linemen (36.7 hits) and defensive linemen (31.6 hits) compared with all other positions (p < .001, η2 = .247). Study outcomes determined players/positions most at risk for concussion due to head impacts, which is beneficial in forming concussion prevention and assessment strategies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".