Head Acceleration Events Sustained During High School Wrestling Matches: Grappling With Differences Between Male and Female Adolescents
Bibliographic record
Abstract
Wrestling is a popular high school sport despite high injury and concussion rates. Instrumented mouthguards can reliably measure head acceleration events (HAEs) accrued by wrestlers and may highlight potential sex differences; important considering the higher concussion rates among female athletes. The purpose of this study was to measure HAEs accrued in high school wrestling matches and compare frequency, magnitude, and head impact location between female and male wrestlers. Forty-five (16.5 [0.8] y) wrestlers (20 females; 25 males) wore instrumented mouthguards during high school matches. A total of 2843 (857 females; 1986 males) HAEs above an 8g trigger threshold from 452 player-matches were video verified. Results indicate that males accrue 30% higher HAE count per match (mean frequency = 6.9 HAEs/match) compared to females (mean frequency = 5.3 HAEs/match) (IRR = 1.297; 95% confidence interval, 1.051-1.594). Results also show females and males have similar HAE biomechanics including peak linear acceleration, angular velocity and acceleration, change in angular velocity in all planes, and impulse duration. Finally, females accrue 50% more head impacts high and to the right side of the head than males (IRR = 1.499; 95% confidence interval, 1.053-2.137). Higher HAE match counts for male wrestlers and varied impact locations highlight varied wrestling HAE mechanisms for female and male adolescent wrestlers and potential sex-specific HAE and concussion prevention 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".