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Record W2068605703 · doi:10.1260/026309207783700394

Multi-Axis Sinusoidal Whole-Body Vibrations: Part II — Relationship between Vibration Total Value and Discomfort Varies between Vibration Axes

2007· article· en· W2068605703 on OpenAlexaff
James P. Dickey, Tammy Eger, Michele Oliver, Paul-Émile Boileau, Lana M. Trick, A. Michelle Edwards

Bibliographic record

VenueJournal of low frequency noise, vibration and active control · 2007
Typearticle
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsInstitut de recherche Robert-Sauvé en santé et en sécurité du travailLaurentian UniversityUniversity of Guelph
Fundersnot available
KeywordsVibrationWhole body vibrationWeightingEquivalence (formal languages)MathematicsStructural engineeringVibration of platesAcousticsPhysicsEngineering

Abstract

fetched live from OpenAlex

The influence of vibration duration and the amount of rest between successive vibrations was addressed in Part I of this study. The relationship between discomfort and Vibration Total Value for different axes of vibration is assessed in Part II. Ten subjects were exposed to repeated single axis, planar, and 6 degree of freedom multi-axial vibrations. We observed statistically significant differences in discomfort between the different axes of vibration for similar ranges of Vibration Total Values. In particular. we observed that discomfort reports for vibrations in the Z axis and XY plane were less than discomfort reports associated with XZ plane and 6 df vibrations when the same range of Vibration Total Values were compared. Furthermore, single axis vertical vibrations were typically associated with less discomfort than multi-axis vibrations when similar ranges of Vibration Total Values were compared. This finding infers that the frequency weighting scheme presented in ISO 2631–1 does not achieve inter-axis equivalence and indicates that a more comprehensive study of multi-axis vibration is required to suggest changes to the ISO 2631–1 weighting factors.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.004
Open science0.0000.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.313
Teacher spread0.288 · 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 designObservational
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

Citations23
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueJournal of low frequency noise, vibration and active controlSame topicEffects of Vibration on HealthFrench-language works237,207