Investigating small RPAS ground impact injury severity criteria (phase 1 report)
Bibliographic record
Abstract
The project was focused on investigating sRPAS to human head impact safety. A finite element (FE) model of a representative quadcopter sRPAS was developed. The FE sRPAS model impacted average adult male model and head kinematics data were predicted. The model predictions were validated against cadaveric data. Based on validated computational simulations, various injury metrics including HIC (head injury criteria), BrIC (brain injury criteria), peak head linear accelerations, and peak rotational velocity were analyzed. A strong correlation between HIC15 and peak linear acceleration was observed. Also, BrIC strongly correlated with peak rotational velocity. Minimizing the structural effect of the quadcopter sRPAS, HIC15 was found to positively correlate with skull stresses. BrIC was found to be moderately correlated with brain strains evaluated using cumulative strain damage measure (CSDM). Sensitivity analysis on impact location and impact angle revealed that head kinematics would be affected by slight changes of impact location and impact angle. Head kinematics, HIC, BrIC, skull stress, and brain strain were compared between average male and small female using computational simulations. Small female head experienced almost twice of HIC and 40% more BrIC as average female head experienced.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".