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Record W2063266282 · doi:10.1121/1.1632091

Interlaboratory comparison of microphone calibration

2004· article· en· W2063266282 on OpenAlexaffabout
George S. K. Wong, Lixue Wu

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2004
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Measurement and Uncertainty Evaluation
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsCalibrationMetrologyMicrophoneStandard deviationStandard uncertaintyAcousticsNational standardReference valuesStatisticsComputer scienceMathematicsMeasurement uncertaintyPhysicsMedicineEngineering

Abstract

fetched live from OpenAlex

The results of an interlaboratory comparison on microphone calibration involving five National Metrology Institutes (NMIs) are presented. The Institute for National Measurement Standards (INMS-Canada), was the pilot laboratory that provided the data analysis for this investigation. The final results presented here were discussed and agreed upon by all participants. The maximum rms deviation for the two LS1P laboratory standard microphones measured by the above participants is 0.037 dB, which may be considered as the key comparison reference value.

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)0.058
metaresearch head score (Gemma)0.127
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 score0.058
Threshold uncertainty score0.307

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0580.127
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.003
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0030.006
Research integrity0.0030.001
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 head0.115
GPT teacher head0.386
Teacher spread0.271 · 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

Citations5
Published2004
Admission routes2
Has abstractyes

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Same venueThe Journal of the Acoustical Society of AmericaSame topicScientific Measurement and Uncertainty EvaluationFrench-language works237,207