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Record W2038534109 · doi:10.1121/1.2947625

Quantifying the through-thickness asymmetry of sound absorbing porous materials

2008· letter· en· W2038534109 on OpenAlexafffund
Yacoubou Salissou, Raymond Panneton

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2008
Typeletter
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsUniversité de Sherbrooke
FundersFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsAsymmetryMaterials sciencePorosityAcousticsElectrical impedancePorous mediumAcoustic impedanceMechanicsComposite materialPhysics

Abstract

fetched live from OpenAlex

A method to quantify the through-thickness asymmetry of a sound absorbing porous material is proposed and discussed. Its calculation only requires impedance tube measurements of the acoustical surface impedance performed on both sides of the tested material. The method may be used for quality control or to assess the level of asymmetry of the material in terms of its acoustic properties. As a first validation, a two-layered porous system seen as an equivalent asymmetrical single porous layer with a sudden change in its physical properties is studied. From this study, a criterion of asymmetry is suggested and experimentally tested.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.812
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0010.004
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 head0.042
GPT teacher head0.284
Teacher spread0.242 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2008
Admission routes2
Has abstractyes

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