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Record W2311363641 · doi:10.7205/milmed.171.10.976

Auditory Perception with Ear and Cold Weather Face Protection Worn in Combination

2006· article· en· W2311363641 on OpenAlexaff
Sharon M. Abel, Patricia Odell

Bibliographic record

VenueMilitary Medicine · 2006
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsAudiologyHearing protectionCold weatherMedicineHearing lossAttenuationConsonantAcoustic attenuationQUIETAcousticsAtmospheric sciencesPhysicsSpeech recognitionComputer science

Abstract

fetched live from OpenAlex

The effects on hearing thresholds, sound attenuation, and consonant discrimination of wearing a balaclava under hearing-protecting earmuffs were studied. This combination is commonly worn during cold weather military operations. One group of 20 normal-hearing adults (10 male and 10 female subjects) was tested. Within-subject measurements were made of diffuse-field hearing thresholds from 0.25 kHz to 8 kHz and consonant discrimination in quiet with the ears unoccluded and protected with the earmuffs alone and with the balaclava worn full face or rolled. Attenuation was derived from the protected and unoccluded thresholds at each frequency. When the balaclava was worn full face, attenuation decreased by 16 to 18 dB, relative to the muff alone, below 6.3 kHz. With the balaclava worn as a cap, there was an inverted U-shaped decrement in attenuation of 18 to 27 dB from 0.25 Hz to 4 kHz. Consonant discrimination decreased by 7% with the muffs alone. These findings underscore the importance of assessing protective equipment under the conditions in which it will be worn.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.018
GPT teacher head0.309
Teacher spread0.291 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2006
Admission routes1
Has abstractyes

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