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Record W4400613289 · doi:10.1016/j.apergo.2024.104343

Assessing the multidimensional comfort of earplugs in virtual industrial noise environments

2024· article· en· W4400613289 on OpenAlexafffund
Olivier Valentin, Said Ezzaf, Philippe-Aubert Gauthier, Djamal Berbiche, Alessia Negrini, Olivier Doutres, Franck Sgard, Alain Berry

Bibliographic record

VenueApplied Ergonomics · 2024
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsUniversité de SherbrookeUniversité du Québec à MontréalInstitut de recherche Robert-Sauvé en santé et en sécurité du travailÉcole de Technologie SupérieureMcGill UniversityCentre for Interdisciplinary Research in Music Media and Technology
FundersInstitut National de Recherche et de SécuritéMitacsInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du TravailUniversité de SherbrookeInstitut de recherche Robert-Sauve
KeywordsDimension (graph theory)ReplicatePerceptionNoise (video)Computer scienceEngineeringSimulationPsychologyArtificial intelligenceStatisticsMathematics

Abstract

fetched live from OpenAlex

Earplugs' comfort is primarily evaluated through cost-effective laboratory evaluations, yet these evaluations often inadequately capture the multidimensional comfort aspects due to design limitations that do not replicate real-world conditions. This paper introduces a novel laboratory method for comprehensive assessment of the multidimensional comfort aspects of earplugs, combining questionnaire-based evaluations and objective perceptual tests within virtual industrial sound environments replicating in-situ noise exposure. Objective perceptual results confirm that the sound environment affect participants' ability to detect alarms in a noisy environment and comprehend speech-in-noise while wearing earplugs. Subjective questionnaire results reveal that the earplugs family has an effect on the primary attributes of the acoustical, physical and functional comfort's dimension. Participants reported the physical dimension as the most important factor they take into account when evaluating earplugs' comfort. The functional dimension was considered the second most important factor by the participants, followed by the psychological dimension, and the acoustical dimension.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.708
Threshold uncertainty score0.391

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 integrity0.0000.001
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 head0.055
GPT teacher head0.369
Teacher spread0.314 · 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 designNot applicable
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

Citations5
Published2024
Admission routes2
Has abstractyes

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