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Record W1767306909

Whole-body vibration in military vehicles: A literature review

2005· review· en· W1767306909 on OpenAlexaffvenue
Ann Nakashima

Bibliographic record

VenueCanadian acoustics · 2005
Typereview
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsWhole body vibrationVibrationCognitionComputer scienceEngineeringNoise (video)Effects of sleep deprivation on cognitive performanceSimulationPsychologyAcousticsArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

Military personnel are exposed to high levels of whole-body vibration in armoured vehicles. Since command and control operations are likely to become more mobile in the future, it is of interest to understand the effects of whole-body vibration exposure on human performance and communication. This paper is a review of the effects of whole-body vibration on hearing and cognitive performance. Exposure to vibration has been shown to exacerbate noise-induced hearing loss, which may have implications for radio communication and speech understanding. Vibration does not appear to affect performance for simple cognitive tasks, but it may degrade performance on more complex cognitive tasks, particularly if the exposure is of long duration. This could be of key importance in a command and control situation, in which operators are under high cognitive load. The severity of vibration that is experienced in armoured vehicles makes it difficult to perform realistic experiments in the laboratory, meaning that future studies of its effects on cognitive performance and communication will likely have to be performed in the field.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.526
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.042
GPT teacher head0.404
Teacher spread0.362 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations8
Published2005
Admission routes2
Has abstractyes

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