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Record W3097427119 · doi:10.11159/cdsr20.156

Injury Risk and Comfort Assessment Applied to AmbulanceTransportation

2020· article· en· W3097427119 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings of the International Conference of Control, Dynamic systems, and Robotics · 2020
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsCarleton University
Fundersnot available
KeywordsMedical emergencyComputer scienceTransport engineeringAeronauticsEngineeringMedicine

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.316
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.040
GPT teacher head0.364
Teacher spread0.324 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it