Factors Influencing the Oblique Impact Test of Motorcycle Helmets
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: Oblique impact tests can provide important information regarding the level of protection of a helmet. Two factors that influence the results of oblique impact tests on motorcycle helmets are discussed in this work. The first factor is the angle of the anvil on which the helmet impacts. The second one is the friction between the headform and the helmet's interior. METHODS: To study the first factor, 2 anvil angles are provided, one 30° and the other one 15° to the vertical. To analyze the second factor, we consider 2 types of headform surfaces: the original metal surface of the standard headform and the same headform covered uniformly with a layer of silicone rubber that is 1 mm thick. RESULTS: The results show that varying the anvil's angle and surface friction can directly affect the linear and rotational acceleration of the headform. CONCLUSION: Testing helmets for different oblique impact angles can help assess their protection capability. The coefficient of friction between the helmet's interior and the headform plays an important role in the headform's rotational acceleration during an impact. Using a standard surface friction for headform similar or close to that of the human scalp can ensure that the results of the oblique impact tests are more consistent and realistic.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 it