A New Biofidelic Sagittal Plane Surrogate Neck for Head-First Impacts
Bibliographic record
Abstract
OBJECTIVE: To evaluate a prototype sagittal plane surrogate neck model designed to provide a biofidelic response to head-first impacts with a straightened cervical posture. METHODS: Published biomechanical studies were used in the design to define the range of motion (ROM) and stiffness in both flexion-extension rotation and axial compression. The neck was tested in a series of head-first impacts on a drop tower to investigate the temporal aspects of the kinetic axial force response for the head and neck. A separate series of flexion-extension tests was conducted in a spinal motion simulator to assess its ROM and bending stiffness. RESULTS: In impacts with a 104 N axial preload, the surrogate head and neck displayed a bimodal response to force development in agreement with published studies of cadaveric head-first impacts. In bending without an axial preload, the neck had an ROM and bending stiffness representative of cadaveric human spines and it included a large neutral zone, but with the incremental addition of axial preload these metrics were somewhat reduced. CONCLUSIONS: The model appears suitable for studying the scenario of sagittal plane, aligned column impacts. Further design refinements are required to provide biofidelity in both sagittal bending and head-first impacts using a single level of axial preload. This would be necessary to study impact scenarios where considerable sagittal plane neck rotation occurs at impact. The model has identified some key concepts that must be considered for continued design and improvement of a dedicated dummy neck for head-first impacts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".