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Record W7132685171

Estimating the resonant transmission loss to calculate the apparent sound transmission class rating of lightweight building constructions

2019· article· en· W7132685171 on OpenAlexvenueaboutno aff
J. Mahn

Bibliographic record

VenueNPARC · 2019
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsnot available
Fundersnot available
KeywordsFlanking maneuverTransmission (telecommunications)Sound transmission classTransmission lossPath (computing)Data transmission
DOInot available

Abstract

fetched live from OpenAlex

The standard, ISO 12354 requires that for each flanking transmission path involved in the calculation of the apparent transmission loss, the sound reduction index of the involved elements should relate to the resonant transmission only. The Standard indicates that the calculation of the resonant transmission should be made using the radiation efficiencies measured with airborne and structure-bore excitation. The Standard indicates that for double leaf elements, the difference between the resonant and measured transmission loss is small but is this true in practice? And what is the consequence of not calculating the resonant transmission loss correctly? Data is presented which compares calculations of flanking transmission for individual flanking paths using data measured for individual elements and junctions with measurements of flanking transmission for identical constructions in the eight room flanking facility at the National Research Council Canada to determine the importance of the calculation of the resonant transmission loss.

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)0.002
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.254
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 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

Citations0
Published2019
Admission routes2
Has abstractyes

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Same venueNPARCSame topicAcoustic Wave Phenomena ResearchFrench-language works237,207