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Record W4252298647 · doi:10.1121/1.4800065

Implementation of a simplified, artificial external ear test fixture for measurement of the earplug induced auditory occlusion effect

2013· article· en· W4252298647 on OpenAlexafffund
Martin Brummund, Franck Sgard, Yvan Petit, Frédéric Laville, J. Boutin

Bibliographic record

VenueProceedings of meetings on acoustics · 2013
Typearticle
Languageen
FieldMedicine
TopicEar Surgery and Otitis Media
Canadian institutionsÉcole de Technologie Supérieure
FundersInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsTest fixtureAuditory canalFixtureOcclusionComputer scienceEar canalAcousticsAudiologyIncusBiomedical engineeringOuter earMaterials scienceMiddle earEngineeringStapesMedicineAnatomySurgeryMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

Earplugs remain a frequently used short-term solution for occupational hearing conservation. Due to comfort limitations, as induced by e.g. the occlusion effect, workers often only wear earplugs for limited amounts of time and are likely to develop professional hearing loss. The occlusion effect expresses itself in the low frequencies through an altered perception of the wearer's own voice and the amplification of physiological noises that occur upon earplug insertion. While many studies examined the occlusion effect experimentally, no study was found that attempted to implement an artificial external ear model dedicated to the measurement of the objective occlusion effect. A simplified external ear test fixture can help to better assess and design earplugs, because it allows standardized experimental testing. This work describes the implementation of a cylindrical artificial test fixture of the human outer ear that comprises the auditory canal as well as the bony, cartilaginous, and skin tissues that are made up of rigid polyurethane foam and two different types of silicone, respectively. Obtained measurement results are compared to literature findings.

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)0.003
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 head0.017
GPT teacher head0.272
Teacher spread0.254 · 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
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of meetings on acousticsSame topicEar Surgery and Otitis MediaFrench-language works237,207