MétaCan
Menu
Back to cohort
Record W4415455431 · doi:10.3397/in_2025_1084843

Low-Frequency Impact Sound Insulation Descriptors Considering CLT Floors: ISO and ASTM Standards

2025· article· en· W4415455431 on OpenAlexaff
Mohamad Bader Eddin, Cheng Qian, Sylvain Ménard, Jean-Luc Kouyoumji

Bibliographic record

VenueNOISE-CON proceedings · 2025
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsFPInnovationsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsSoundproofingSound pressureNatural rubberTappingCorrelationCross-correlationEvaluation methods

Abstract

fetched live from OpenAlex

Impact sound insulation performance is evaluated using weighted normalized impact sound pressure level (Ln,w) per ISO 717-2 and Impact Insulation Class (IIC) per ASTM E989, both measured using a standardized tapping machine in one-third-octave bands from 100-3150 Hz. Impact sounds below 100 Hz are correlated with subjective human annoyance. To account for low-frequency performance, these standards introduce additional descriptors, such as spectrum adaptation terms (CI,50-2500) in ISO and Low Impact Insulation Class (LIIC) in ASTM. Another test method involves the ISO rubber ball, which closely resembles the excitation of human hearing in the low-frequency range. The resulting spectrum performance is expressed by the standardized maximum impact sound pressure level (LAFmax,V,T). This study examines the correlation between low-frequency impact sound insulation descriptors in ISO and ASTM standards. Various laboratory-based impact sound insulation measurements were conducted on different CLT floor assemblies using both a standardized tapping machine and a rubber ball. ISO and ASTM acoustic descriptors are plotted against LAFmax,V,T. The results show a strong correlation between tapping machine and rubber ball measurements in ISO standards. However, no correlation is observed between LIIC and LAFmax,V,T. Finally, the necessity of considering both standards' descriptors in describing low-frequency impact sound performance is discussed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.707
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.271
Teacher spread0.259 · 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 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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueNOISE-CON proceedingsSame topicAcoustic Wave Phenomena ResearchFrench-language works237,207