Injury Risk and Comfort Assessment Applied to AmbulanceTransportation
Bibliographic record
Abstract
Speed humps are an effective means to moderate the speed of traffic but can have adverse effects on the circulation of emergency vehicles. This study aims to use various comfort and injury risk metrics to evaluate the effects of speed hump traversal on the comfort of the passengers. Studies of human comfort during ambulance transport typically consider the peak acceleration and the wholebody vibration dose value from ISO 2631-1. The novel application of other metrics in the ambulance transport scenario, which were derived for naval and aviation settings, provided additional insight to the human biodynamic response and comfort. The following parameters were considered in the study: peak seat acceleration, dynamic response index, peak lumbar acceleration, bandwidth-limited power-spectral density, and the average acceleration onset derivative (average jerk). In-vehicle road tests were conducted in a Type III ambulance on flat-top and sinusoidal speed humps at various traversing speeds. Results from this experiment show that speeds over 20 km/hr will result in some degree of discomfort to passengers in the ambulance. Additional experiments are needed to verify the consistency of these parameters, but this study has provided a proof of concept for further studies.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".