Comparison of Head Impact Biomechanics across Multiple Sports
Bibliographic record
Abstract
<div>Athletes may sustain numerous head impacts during sport, leading to potential neurological consequences. Wearable sensors enable real-world head impact data collection, offering insight into sport-specific brain injury mechanisms. Most instrumented mouthguard studies focus on a single sport, lacking a quantitative comparison of head impact biomechanics across sports. Additionally, direct comparison of prior studies can be challenging due to variabilities in methodology and data processing. Therefore, we gathered head impact data across multiple sports and processed all data using a uniform processing pipeline to enable direct comparisons of impact biomechanics. Our aim was to compare peak kinematics, impulse durations, and head impact directionality across ice hockey, American football, rugby, and soccer. We found that American football had the highest magnitude of head impact kinematics and observed directionality differences in linear and angular kinematics between sports. On the other hand, there were no significant differences in impulse durations, which was unexpected given the different impacting objects and protective equipment across sports. In future work, we aim to expand our dataset to better match sports for understanding the influence of sex, equipment, and playstyle on head impact biomechanics.</div>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".