Estimating the Influence of Neckform Compliance on Brain Tissue Strain During a Helmeted Impact
Bibliographic record
Abstract
The aim of this study was to determine if a change in neckform compliance could influence maximum principal strain in the brain white and grey matter, the brain stem and the cerebellum. This was done by impacting a Hybrid III headform with a 16.6 kg impactor arm at 5 m/s. Three different Hybrid III neckforms were used: 1) one 50th percentile male neckform - standard neckform; 2) one 50th percentile male neckform plus 30 per cent compliance - soft neckform; 3) one 50th percentile male neckform minus 30 per cent compliance - stiff neckform. The kinematic data obtained was then used to drive a finite element model developed by University College Dublin. The results showed that a decrease in neckform compliance had a significant effect on maximal principal strain in the cerebellum, where the stiff neck (0.050 ± 0.004) generated higher maximum principal strains than the standard neck (0.036 ± 0.003) and the soft neck (0.037 ± 0.001). There were no significant differences between the stiff (0.122 ± 0.013), standard (0.114 ± 0.020) and soft neck (0.119 ± 0.019) in the white matter; the stiff (0.168 ± 0.011), standard (0.176 ± 0.011) and soft neck (0.176 ± 0.007) in the grey matter; or the stiff (0.080 ± 0.003), standard (0.081 ± 0.006) and soft neck (0.085 ± 0.009) in the brain stem. The results were not linked to brain injury due to the absence of a commonly accepted threshold.
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How this classification was reachedexpand
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 teacher head, 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".