Implementation of Child Biomechanical Neck Behaviour into a Child FE Model
Bibliographic record
Abstract
<div class="htmlview paragraph">This research focuses on the further development of a child finite element model whereby implementation of pediatric cadaver testing observations considering the biomechanical response of the neck of children under tensile and bending loading has occurred. Prior to this investigation, the biomechanical neck response was based upon scaled adult cadaver behaviour. Alterations to the material properties associated with ligaments, intervertebral discs and facet joints of the pediatric cervical spine were considered. No alteration to the geometry of the child neck finite element model was considered. An energy based approach was utilized to provide indication on the appropriate changes to local neck biomechanical characteristics. Prior to this study, the biomechanical response of the neck of the child finite element model deviated significantly from the tensile and bending cadaver tests completed by Ouyang et al. After alteration of the neck biomechanical behaviour was completed the neck tensile force was observed to be within the range of the cadaver tests and the rotation-moment response was in good agreement to the corridor of the pediatric cadaver tests. Utilizing the improved neck model into the child finite element model simulating a FMVSS 213 test resulted in an increase in tensile deformation of on the order of three times and rotational deformation of approximately 37%. Head and chest accelerations from both the child models before and after the neck alterations however remained similar. An important qualitative finding from this investigation indicated that the improved child model appeared to predict an atlanto-occipital dislocation which was observed to occur (in a similar crash condition) to a 23 month-old child. This research was completed in an effort to improve the biofidelity of the child model and the accuracy of child injury prediction in forward facing child restraint seats during numerical simulation of frontal crashes.</div>
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".