Comparison of two anthropomorphic test devices using brain motion
Bibliographic record
Abstract
The use of anthropomorphic test devices in head impact biomechanics research is common; however, each device has unique properties based on its construction. When conducting reconstructions, choice of head form is at the discretion of the researcher. In addition, different data collection methods are often used. The influence of different test devices can affect comparisons between studies, as each device elicits different impact responses due to different physical properties. This study describes a method of comparison for anthropomorphic test devices based on finite element response of brain motion. Occipital impacts were conducted on a monorail drop rig, following impact parameters similar to a cadaveric impact that has been used for validation of finite element models of the brain. Two commonly used anthropomorphic test devices, the Hodgson-WSU and Hybrid III, were impacted. These head forms were evaluated by dynamic responses, brain motion via neutral density target traces, and maximum principal strain for two impact velocities. The Hybrid III head form showed lower magnitude results compared to the Hodgson-WSU for peak linear and rotational accelerations, rotational velocity, maximum principal strain, and neutral density target excursions. The smallest differences in response were 11% for peak linear acceleration with differences in neutral density target excursions reaching 60%. Maximum principal strain is suggested as the most comparable metric between anthropomorphic test devices after peak linear acceleration, with expectation of lower responses from the Hybrid III as compared to those of the Hodgson-WSU.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".