Interaction of external head impact parameters on region and volume of strain for collisions in sport
Bibliographic record
Abstract
Collisions with the head are the primary cause of concussion in contact sports. Head impacts can be further characterized by velocity, striking mass, compliance, and location (direction). The purpose of this study was to describe the interaction effects of these parameters on peak strain in four brain regions and the volume of strain for collision impacts. A pendulum test set-up was used to deliver impacts to an adult Hybrid III headform according to four levels of mass (3, 9, 15, and 21 kg), four velocities (1.5, 3.0, 4.5, and 6.0 m/s), two impact locations (through the centre of gravity and a non-centre of gravity), and three levels of compliance simulating unprotected, helmeted, and well-padded conditions in sport. Headform accelerations were input into a brain finite element model to obtain peak strain in the frontal, temporal, parietal, and occipital lobes and the volume of the brain experiencing 0.10, 0.15, 0.20, and 0.25 strains. Centre-of-gravity impacts created the highest strains (peak and volume) under low compliance and non-centre-of-gravity impacts produced greater strain responses under medium and high compliance conditions. The temporal lobe was the region that consistently displayed the highest peak strains, which may be due to the proximity of the impact locations to this region. Interactions between mass and velocity displayed effects where the 9-kg mass had higher peak and volumes of strain than the 15-kg mass at velocities of 3.0 and 4.5 m/s. This study demonstrates the important role of interacting impact parameters on increasing strain responses that are relevant to the spectrum of diffuse brain injuries, including concussion.
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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 | 0.001 |
| 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) | 0.002 | 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".