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Record W3028565403 · doi:10.1088/0026-1394/57/1a/09002

Final report on supplementary regional comparison SIM.AUV.A-S2: calibration of pistonphone

2020· article· en· W3028565403 on OpenAlexaffabout
Thiago Antônio Bacelar Milhomem, Zemar Martins Defilippo Soares, Gustavo P. Ripper, J P Ayala, G M Guevara, F. Serrano, A. Solano, Rozenn Wagner, Peter Hanes

Bibliographic record

VenueMetrologia · 2020
Typearticle
Languageen
FieldEngineering
TopicFlow Measurement and Analysis
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMutual recognitionMetrologyNISTCalibrationDistortion (music)MathematicsTotal harmonic distortionStatisticsComputer scienceTelecommunicationsEngineeringElectrical engineeringSpeech recognition

Abstract

fetched live from OpenAlex

This document is the Final Report of the Inter-American Metrology System supplementary comparison on pistonphone calibration SIM.AUV.A-S2. Seven national metrology institutes participated on this comparison: CENAM/Mexico, INACAL/Peru, INMETRO/Brazil, INTI/Argentina, LACOMET/Costa Rica, NIST/USA and NRC/Canada and INMETRO was the pilot institute responsible for its coordination. One pistonphone was circulated among the participants to carry out calibrations according to the international standard IEC 60942:2017 using both LS1P and LS2P measurement microphones. Beyond the mandatory measurement of the sound pressure level, it was requested to the participants report measurement results of frequency, total harmonic distortion and total distortion + noise for the purpose of investigation. For sound pressure level and frequency measurement results, supplementary comparison reference values (SCRVs) were determined using the weighted mean method and the corresponding degrees of equivalence obtained between each participant and the SCRV are presented. For total harmonic distortion and total distortion + noise measurements, SCRVs were not calculated and the values reported by participants are compared with the calculated arithmetic mean and weighted mean values. Overall, the supplementary comparison SIM.AUV.A-S2 was considered successful and fits its purpose. Main text To reach the main text of this paper, click on Final Report . Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/ . The final report has been peer-reviewed and approved for publication by the CCAUV, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

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)0.009
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.352
Threshold uncertainty score0.924

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0020.000
Scholarly communication0.0030.003
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.3520.211

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 head0.072
GPT teacher head0.258
Teacher spread0.186 · 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.

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".

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Citations0
Published2020
Admission routes2
Has abstractyes

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