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Record W1891837411

The ANSI standard S12. 68-2007 method of estimating effective a-weighted sound pressure levels when hearing protectors are worn: A canadian perspective

2008· article· en· W1891837411 on OpenAlexaffvenueabout
Jérémie Voix, Alberto Behar, Willy Wong

Bibliographic record

VenueCanadian acoustics · 2008
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSound pressureAttenuationComputer sciencePercentileAcousticsAcoustic attenuationPerspective (graphical)Standard deviationField (mathematics)TelecommunicationsStatisticsMathematicsArtificial intelligencePhysics
DOInot available

Abstract

fetched live from OpenAlex

The Canadian ANSI standard S12.68-2007 method has been developed as a method of estimating effective A-weighted sound pressure levels after wearing hearing protective devices (HPD). The two percentile values would represent the sound attenuation that most individually trained users to achieve or exceed and that a few motivated proficient users to achieve or exceed. The Canadian workplaces of the NOISH 100 spectrum is used and a comprehensive analysis is conducted by Berger and Gauger. A field validation of Canadian workplace is required and would consist in the statistical comparison of field attenuation data. The developments of ANSI standard S12.68-2007 method provides 3 different practical tools to estimate from laboratory data the attenuation that user achieve in the field. The use and reference of ANSI standard S12.68-2007 method by the Canadian standards could be considered, after successful conduction of validation.

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)0.011
metaresearch head score (Gemma)0.019
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: none
Teacher disagreement score0.100
Threshold uncertainty score0.201

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.019
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.007
Science and technology studies0.0030.003
Scholarly communication0.0040.001
Open science0.0060.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.004

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 head0.047
GPT teacher head0.365
Teacher spread0.318 · 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

Citations19
Published2008
Admission routes3
Has abstractyes

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