A Biofidelity Evaluation of the BioRID II, Hybrid III and RID2 for Use in Rear Impacts
Bibliographic record
Abstract
In this study, three dummies were evaluated on the component level and as a whole. Their responses were compared with available volunteer and embalmed Post Mortem Human Subject (PMHS) data obtained under similar test conditions to evaluate their biofidelity. The volunteer and PMHS data, used as comparators in this study, were used previously to establish some of the biofidelity requirements of the Hybrid III. The BioRID II, the Hybrid III, and the RID2 were all subjected to rear impact HYGE sled tests with deltaVs of 17 and 28 km/hr to determine their biofidelity in these conditions. A static pull test, where a load was manually applied to the head of each dummy, was used to evaluate the static strength of their necks in flexion and extension. Finally, pendulum tests were conducted with the Hybrid III and RID2 to evaluate the dynamic characteristics of their necks in flexion and extension. The sled test results indicate that out of the three dummies, the overall flexibility of the Hybrid III is comparable to that of the volunteer anticipating the impact. The overall flexibilities of the BioRID II and the RID2 are greater than those of all the comparators used in this study (the tensed volunteer and the two embalmed PMHSs). The responses of the Hybrid III are closer to those of the tensed volunteer than those of the PMHSs. The responses of the BioRID II and the RID2 are closer to those of the PMHSs than to the tensed volunteer.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".