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Record W2590954857 · doi:10.1121/1.4976087

How reproducible is the acoustical characterization of porous media?

2017· article· en· W2590954857 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2017
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsUniversité de SherbrookeInstitut de recherche Robert-Sauvé en santé et en sécurité du travail
Fundersnot available
KeywordsReproducibilityCharacterization (materials science)Porous mediumPorosityWork (physics)AcousticsMaterials scienceComputer scienceMechanical engineeringPhysicsNanotechnologyMathematicsStatisticsComposite materialEngineering

Abstract

fetched live from OpenAlex

There is a considerable number of research publications on the characterization of porous media that is carried out in accordance with ISO 10534-2 (International Standards Organization, Geneva, Switzerland, 2001) and/or ISO 9053 (International Standards Organization, Geneva, Switzerland, 1991). According to the Web of ScienceTM (last accessed 22 September 2016) there were 339 publications in the Journal of the Acoustical Society of America alone which deal with the acoustics of porous media. However, the reproducibility of these characterization procedures is not well understood. This paper deals with the reproducibility of some standard characterization procedures for acoustic porous materials. The paper is an extension of the work published by Horoshenkov, Khan, Bécot, Jaouen, Sgard, Renault, Amirouche, Pompoli, Prodi, Bonfiglio, Pispola, Asdrubali, Hübelt, Atalla, Amédin, Lauriks, and Boeckx [J. Acoust. Soc. Am. 122(1), 345–353 (2007)]. In this paper, independent laboratory measurements were performed on the same material specimens so that the naturally occurring inhomogeneity in materials was controlled. It also presented the reproducibility data for the characteristic impedance, complex wavenumber, and for some related pore structure properties. This work can be helpful to better understand the tolerances of these material characterization procedures so improvements can be developed to reduce experimental errors and improve the reproducibility between laboratories.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.903
Threshold uncertainty score0.623

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.262
Teacher spread0.238 · 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