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Record W2004592166 · doi:10.1121/1.4782001

Characterization of vibration and noise exposure in Canadian Forces armored vehicles

2005· article· en· W2004592166 on OpenAlexaffabout
Ann Nakashima, Matthew James Borland, Sharon M. Abel

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2005
Typearticle
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsCrewAeronauticsNoise (video)Whole body vibrationVibrationTerrainStandardizationAutomotive engineeringEnvironmental scienceMarine engineeringComputer scienceAcousticsEngineeringPhysicsGeography

Abstract

fetched live from OpenAlex

A study to characterize the vibration and noise exposure in several Canadian Forces (CF) armored vehicles is in progress. Measurements of whole-body vibration and ambient noise levels are being made in the LAV III, Bison, Coyote, and M113 vehicles at three different positions: driver, crew commander, and passenger bench (or navigator seat in the case of the Coyote). The measurements are being made while the vehicles are idling, driven over rough terrain, and driven at a high speed on paved highways. There are several standards that provide guidance on the measurement and assessment of whole-body vibration, but they are difficult to implement in practice, particularly in adverse environments. The whole-body vibration measurements in this study are particularly difficult to interpret in the case of the crew commander, who often stands on the seat, and the passenger, who is seated but unrestrained by a seatbelt. The preliminary results-suggest, that according to the International Organization for Standardization guidelines (ISO 2631-1:1997), there may be potential health risks for the driver and passenger after driving on rough terrain for less than 10 min. Noise levels were as high as 100 dBA during high-speed highway driving.

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.

How this classification was reachedexpand

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.893
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.261
Teacher spread0.253 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicEffects of Vibration on HealthFrench-language works237,207