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Record W2622085245 · doi:10.1121/1.4987474

Update on the change in sound insulation requirements in Canada

2017· article· en· W2622085245 on OpenAlexaffabout
Christoph Hoeller, Jeffrey Mahn

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2017
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsSoundproofingSound transmission classPresentation (obstetrics)Sound (geography)Sound changeTransmission (telecommunications)Class (philosophy)Computer scienceCode (set theory)Architectural engineeringTelecommunicationsForensic engineeringEngineeringAcousticsCivil engineeringLinguisticsArtificial intelligenceMedicine

Abstract

fetched live from OpenAlex

In the 2015 edition of the National Building Code of Canada (2015 NBCC, published in January 2016), sound insulation requirements between dwelling units are given in terms of Apparent Sound Transmission Class (ASTC). This is a significant change from the requirements in previous editions of the NBCC which were given in terms of Sound Transmission Class (STC). While the STC rating only accounts for sound transmission through the separating assembly, the ASTC rating also takes into account structural flanking transmission via adjoining building elements. An overview of the change in requirements and of NRC activities to support the code change was given at the ASA meeting in Jacksonville (November 2015). This presentation will provide an update on the implementation of the code change since it came into effect in federal regulations in early 2016. Tools and guidelines provided by the NRC such as Research Report RR-331, “Guide to Calculating Airborne Sound Transmission in Buildings” and the revised version of soundPATHS, NRC’s web application to calculate ASTC ratings, will be presented.

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)0.008
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.062
Threshold uncertainty score0.451

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.028
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.009
Science and technology studies0.0040.001
Scholarly communication0.0050.002
Open science0.0040.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0200.009

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 head0.081
GPT teacher head0.388
Teacher spread0.307 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicNoise Effects and ManagementFrench-language works237,207