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Record W2757977174

TRADING DECIBELS: OVERVIEW OF A CAP AND TRADE REGULATORY FRAMEWORK FOR NOISE EMISSIONS

2017· article· en· W2757977174 on OpenAlexvenueno aff
Donald Christopher Lambert, Samuel Bernard Lacrampe

Bibliographic record

VenueCanadian acoustics · 2017
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsnot available
Fundersnot available
KeywordsNoise controlNoise (video)Environmental economicsEngineeringRisk analysis (engineering)Computer scienceBusinessEconomicsNoise reduction
DOInot available

Abstract

fetched live from OpenAlex

Current regulatory framework and its shortcomingsNoise for energy-related facilities in Alberta is regulated through the Alberta Energy Regulator (AER) Directive 038: Noise Control (the Directive) [1].The goal of the Directive is to reduce the impact of noise received in the environment to a reasonable amount.In its simplest case, the Directive sound level limit is 40 dBA, as measured at the nearest or most impacted residence within 1500 m of a facility.If no residences exist in that zone, then the limit is set at a 1500 m distance.If the facility sound levels are below the limit, then the facility is in compliance, and if above the limit, then the facility is out of compliance.While this approach meets the goal of reducing the noise impact at the receiver to a reasonable level, it still has some shortcomings: i.No incentives to maximize margin of compliance beyond the Directive criteria: In some cases, additional margin of compliance is easily achieved with minimal efforts/expense incurred by the facility owners, and a reasonable investment of noise control can often yield significant benefits in further reducing noise impacts.ii.Inefficiency in Retrofit Noise Control: With a facility operating at the regulatory limit for noise emissions, facility expansions (and/or new proximate facilities) creating additional sound power will often require exceptional noise control (for new equipment), retrofit noise control (for existing equipment), or both.Many industry operators report that retrofit noise control costs can easily exceed ten times the initial capital cost for the same noise control included at the design stage.iii.Little incentive to advance noise control technology: As technologies employed in equipment operation advance and mature over time, it is expected that low noiseemitting equipment becomes more easily available and at a lower cost.However, since the Directive sound level limit is static, there often exists an incentive to deploy equipment that simply meets the limit, rather than installing the latest low-noise-emitting equipment that would optimize the margin of compliance.

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)0.017
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.487
Threshold uncertainty score0.968

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.016
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0080.007
Science and technology studies0.0060.013
Scholarly communication0.0120.007
Open science0.0090.004
Research integrity0.0090.011
Insufficient payload (model declined to judge)0.0110.003

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 head0.120
GPT teacher head0.426
Teacher spread0.305 · 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 designTheoretical or conceptual
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
Published2017
Admission routes1
Has abstractyes

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