Performance analysis of winter activity protection headgear for young children
Bibliographic record
Abstract
OBJECT: The purpose of this study was to evaluate how currently used helmets would perform for winter play activities, such as tobogganing. In Canada and northern parts of the US, the advent of winter is followed by an increase in visits to hospital emergency departments by young children presenting with head injuries resulting from winter activities. Sliding, skating, skiing, and snowboarding all involve risks of head injury from situations such as falling on ice or sliding into stationary objects. This study compared the protective characteristics of helmets used by young children (< 7 years of age) participating in winter recreational activities. METHODS: Ice hockey, alpine ski, and bicycling helmets were impacted at 2.0, 4.0, 6.0, and 8.0 m/second at the front and side impact location by using a monorail drop rig. RESULTS: The results for the front impact showed that the ice hockey helmet protected the child significantly better at 2 and 4 m/second when considering both linear and angular peak acceleration. The bicycle helmet performed significantly better than the other 2 helmets at 8 m/second for the front location and only angularly for the side impacts. CONCLUSIONS: Depending on the impact velocity of the hazard, the type of helmet significantly affected the risk of brain injury.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".