Interaction of impact parameters for simulated falls in sport using three different sized Hybrid III headforms
Bibliographic record
Abstract
This study describes the interaction of impact parameters on peak head acceleration and strain variables for test conditions represented in sport. The Hybrid III 6-year-old child, 5th percentile female, and 50th percentile adult male headforms were subject to parametric tests using a monorail drop tower at four impact velocities (1.5, 3.0, 4.5, and 6.0 m/s), three surfaces (unprotected, protected/helmeted, and well-padded/mat), and four impact locations (frontal, sagittal, combined-plane motions, and a rotationally dominant motion). Scaled finite-element models of the brain were used to obtain peak strains. Regression analyses revealed that compliance produced the greatest increases in head acceleration, while impact velocity was for strain. Smaller headforms were associated with higher responses. Non-uniform trends for impact location were noted and are likely a result of localised headform properties interacting with velocity and compliance. These findings support the need for size-appropriate parameters in the design and development of head protection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 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".