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Record W1894664243

Testing and rating of hearing protector devices - A real headache

2011· article· en· W1894664243 on OpenAlexaffvenueabout
Alberto Behar, Willy Wong

Bibliographic record

VenueCanadian acoustics · 2011
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHearing protectionWork (physics)Property (philosophy)Noise (video)Simple (philosophy)Computer scienceNoise exposureReliability engineeringAudiologyHearing lossEngineeringArtificial intelligenceMedicine
DOInot available

Abstract

fetched live from OpenAlex

Z94.2 is up for review by the Subcommittee SC1 of the Occupational Hearing Conservation Technical Committee S304 of the Canadian Standards Association. The work involves editorial changes as well as updating of the text. The rating of the HPDs, on the other hand, provides a simple way for the calculation of the noise level of the protected ear. It is the parameter used by the safety personnel to choose a protector for a given noisy environment. Another very important HPD property is the comfort experienced by the user. Results from Method A are supposed to represent an optimum fitting scenario that could be accomplished by a motivated and proficient user. Method B, on the other hand, is meant to approximate realistic results for workers in hearing conservation programs. The second option will be to include the existing NRR as rating. NRR was never included in the Z94.2 because of the overly optimistic and unrealistic results.

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)0.024
metaresearch head score (Gemma)0.034
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 score0.971
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.034
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0120.008

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 head0.131
GPT teacher head0.350
Teacher spread0.219 · 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
Published2011
Admission routes3
Has abstractyes

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