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Record W4400288405 · doi:10.1121/10.0026642

Sound flanking through common low-voltage electrical conduit in multi-family residential buildings

2024· article· en· W4400288405 on OpenAlexaffabout
Michael Kundakcioglu, Adam Doiron, Jessica Tinianov

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2024
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsBGC Engineering (Canada)
Fundersnot available
KeywordsElectrical conduitFlanking maneuverSound (geography)AcousticsEnvironmental scienceElectrical engineeringPhysicsEngineeringStructural engineering

Abstract

fetched live from OpenAlex

Sound flanking between suites in multi-family residential buildings is a prevalent issue in architectural acoustics and building construction that can decrease the sound insulation performance of suite-demising partitions, compromising acoustical privacy and comfort for residents. In recent times, a specific deficiency regarding the sealing of common low-voltage electrical conduit routed between residential suites has been increasing in frequency in construction of residential buildings, resulting in otherwise appropriately designed suite demising configurations performing poorly in situ, and in some cases, even failing Ontario Building Code requirements for sound insulation between dwelling spaces during site testing. This article presents test data sampled from multiple residential buildings in Ontario, highlighting the extent of this issue and its implications, along with discussion regarding the proactive prevention and post-construction rectification of this issue.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.294
Teacher spread0.270 · 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 designObservational
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
Published2024
Admission routes2
Has abstractyes

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