Differences in region-specific brain tissue stress and strain due to impact velocity for simulated American football impacts
Bibliographic record
Abstract
Concussion has become a prevalent injury in the sport of American football, and its severity can be influenced by the mass of the impactor, velocity, compliance, and direction of impact. As a result, it is important to characterize how American football helmets perform against these impact characteristics. The purpose of this research is to examine how an American football helmet performs across velocities and impact angles which can occur in the sport of American football. The methods used a combination of Hybrid III headform impacts combined with a finite element modeling approach to find the brain deformation variables known to be associated with concussion. At the 9.5 m/s impacts, the brain deformation metrics showed an increase in risk of concussion. Also, the region of the brain with the largest magnitude deformation shifted with differing velocities when analyzed using maximum principal strain but not von Mises stress. The results indicate that impact conditions (location and velocity) can influence the regional brain strains.
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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 | 0.001 | 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 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".