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Record W2995328599

The Case For Minimum Impact Noise Requirments in The National Building Code of Canada

2019· article· en· W2995328599 on OpenAlexaffvenueabout
Matthew V. Golden, Roderick C. I. MacKenzie

Bibliographic record

VenueCanadian acoustics · 2019
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsSoft dB (Canada)
Fundersnot available
KeywordsNoise (video)EnforcementMandateEngineeringComputer scienceArtificial intelligencePolitical science
DOInot available

Abstract

fetched live from OpenAlex

In the latest 2015 revision of the National Building Code of Canada (NBCC), Section 5.8 and 9.11 underwent significant changes to finally recognize minimum airborne field performance criteria and flanking sound transmission. Yet the revised NBCC again failed to mandate any minimum require- ment for impact noise isolation for multi-family dwellings, several decades after Canada’s interna-tional peers began implementing mandatory minimum requirements. This is despite a stated objec- tive of the Code to provide “noise protection” to building occupants. A recent code change request submitted in 2016 proposed the inclusion of impact noise protection in the NBCC, including mini- mum IIC/AIIC performance levels and methods of demonstrating compliance. In this paper, we present the case for prioritizing and requiring mandatory, minimum impact noise criteria in the NBCC by synthesizing the submitted NBCC Code change request. This includes a summary of previous research related to: the objectives of the Canadian National Building Code with respect to noise; A comparison with other developed countries; Canadian and International dwelling occupant satisfaction surveys concerning residential impact noise; the potential health effects as re- lated to impact noise sound levels and frequency; the structural changes required to the NBCC to introduce mandatory impact noise criteria; suitable criteria and enforcement mechanisms; and the various steps that can and should be taken by the Canadian acoustical community.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.036
GPT teacher head0.389
Teacher spread0.353 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2019
Admission routes3
Has abstractyes

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