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Record W1751910410

CSA appendix on measurement of noise exposure from headsets

2008· article· en· W1751910410 on OpenAlexaffvenue
Alberto Behar, Christian Giguère, Tim Kelsall

Bibliographic record

VenueCanadian acoustics · 2008
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsUniversity of OttawaHatch (Canada)University of Toronto
Fundersnot available
KeywordsHeadsetOctave (electronics)AcousticsNoise (video)Octave bandAttenuationMicrophoneNoise exposureNoise measurementComputer scienceNoise reductionAudiologyPhysicsOpticsHearing lossLoudspeakerArtificial intelligenceMedicine
DOInot available

Abstract

fetched live from OpenAlex

A new appendix to CSA standard Z107.56 is developed to cover measurements of noise exposure from employees wearing headsets for communication. An alternative indirect calculation method is also proposed that includes the main determinants of exposure as input parameters into the assessment, such as background noise and the attenuation of the device. A microphone is located in the ear simulator of the manikin, and the acoustic measurements are performed in 1/3-octave bands. The alternate calculation method shows that the noise reduction of the headset is assumed to be zero unless the manufacturer can provide user fit octave band attenuation data. The results also show that if the headset is used more than 1 hr per day, the background noise has less than 1 dB effect on the result.

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)0.003
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.130
Threshold uncertainty score0.436

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.1300.091

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 head0.033
GPT teacher head0.210
Teacher spread0.177 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations4
Published2008
Admission routes2
Has abstractyes

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