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Record W1484924634

Measurement of the performance of sound level meters using IEC 61672-3:2006

2007· article· en· W1484924634 on OpenAlexaffvenueabout
Peter Hanes

Bibliographic record

VenueNPARC · 2007
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsSensitivity (control systems)Noise (video)Sound (geography)AcousticsSound level meterIdeal (ethics)Noise levelEngineeringComputer scienceElectronic engineeringSound pressurePhysics
DOInot available

Abstract

fetched live from OpenAlex

IEC 61672-3:2006 provides the first internationally agreed methods for measuring the performance of individual sound level meters (SLM). Pattern approval tests are specified in IEC 61672-2, but are in practice only performed in countries where legal requirements exist for testing a model of SLM before it may be sold. A calibrated sound calibrator is applied in order to determine the overall sensitivity at a reference level at a single frequency. The indicated sound level with no input signal is noted; this corresponds to the level of self-generated noise in the SLM. The indicated peak C sound level in response to single cycle and half cycle sinusoidal electrical signals is measured and compared with the theoretical ideal response. IEC 61672-3 should be recommended for use in Canada with appropriate guidance on its use with respect to older SLMs.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.083
GPT teacher head0.297
Teacher spread0.214 · 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 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

Citations0
Published2007
Admission routes3
Has abstractyes

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