Performance Criteria for a Child-Specific Helmet
Bibliographic record
Abstract
Sport helmets used by children are governed by the same impact performance requirements as those used by adults. Although many standards call for the use of variable-mass head-forms in assessing the suitability of such helmets for protecting against traumatic head injury due to blunt trauma, the failure criterion is the same regardless of head-form size. Using existing literature values for important mechanical and physical characteristics of children's heads (such as skull thickness, strength of skull bone, mass and bulk modulus of the brain, etc.), this paper explores the need for a sport helmet intended specifically for children and some of the important performance criteria required for consideration. A simple model of the head–helmet system is used to suggest that impact protection for children requires a combination of material thickness and density to produce helmet liners that are “softer” than those often used in present-day helmets. Helmet failure criteria based upon the dynamic fracture tolerance of skull bone in children are proposed, and hockey helmets are examined in relation to such by determining the force on the head in targeted impacts of 150 g and 275 g. It is suggested that the current failure limits of 275 g to 300 g used in many helmet standards be reexamined.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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".