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Record W4400287623 · doi:10.1121/10.0026788

Meta-earplugs: Innovative concepts for alleviating the occlusion effect

2024· article· en· W4400287623 on OpenAlexaff
Kévin Carillo, Hugo Saint-Gaudens, Franck Sgard, Olivier Dazel, Olivier Doutres

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2024
Typearticle
Languageen
FieldMedicine
TopicReconstructive Facial Surgery Techniques
Canadian institutionsInstitut de recherche Robert-Sauvé en santé et en sécurité du travailÉcole de Technologie Supérieure
Fundersnot available
KeywordsPsychologyMedicine

Abstract

fetched live from OpenAlex

Passive earplugs are commonly used to reduce workers' exposure to excessively high noise levels. Yet, they are associated with various discomforts of diverse origins (e.g., acoustic, physical, functional, or psychological). The occlusion effect, characterized by an increased perception of physiological sounds transmitted through bone conduction to the cochlea, presents a challenge, leading to acoustic discomfort, especially at low frequencies (0.1 to 1 kHz) and for shallow or moderate insertion depths of the earplug. Building upon acoustic meta-material principles, this study presents “meta-earplug” concepts designed to alleviate the occlusion effect. The approach focuses on reducing the input impedance of the earplug medial surface either to the characteristic impedance of air, using broadband perfect absorption, or to the acoustic impedance of the open ear canal, resulting in a zero objective occlusion effect. For these purposes, the proposed meta-earplug concepts are made of Helmholtz resonators arranged in parallel or series. Transfer matrix models are used in an optimization process to refine the geometry of the meta-earplugs. Although meta-earplug concepts involving multiple Helmholtz resonators have been preliminarily assessed using an artificial ear, a meta-earplug featuring a single resonator has undergone testing with human participants. The evaluation encompasses both objective measurements and subjective assessments.

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)0.003
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.820
Threshold uncertainty score0.390

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.029
GPT teacher head0.341
Teacher spread0.312 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicReconstructive Facial Surgery TechniquesFrench-language works237,207