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Record W2993913474

Learning from evidence of sound experienced from wind turbines

2011· article· en· W2993913474 on OpenAlexvenueaboutno aff
William K. Palmer

Bibliographic record

VenueCanadian acoustics · 2011
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsnot available
Fundersnot available
KeywordsAnnoyanceInfrasoundSound (geography)Disturbance (geology)Wind powerAcousticsNoise (video)TurbineAudiologyEnvironmental scienceEngineeringAeronauticsGeologyComputer scienceMedicineElectrical engineeringPhysicsLoudnessAerospace engineering
DOInot available

Abstract

fetched live from OpenAlex

Wind turbine sound regulations are generally based on A-weighted sound levels, reducing the effect of frequencies outside 500-11,000 Hz by more than 3dB.Wind turbine sound predominates at lower frequencies where human audibility and physiological response still exists.Regulatory limits are not intended to pose annoyance, yet placement of wind turbines near homes is reported to cause significant annoyance, sleep deprivation, and adverse effects.Large industrial wind turbines produce a unique sound signature, cyclical in both amplitude and frequency, from a source that varies in a cyclical pattern of position and distance relative to listening points, since the principal sound source arises from turbulence following the trailing edge of the outer quarter of the blades, an annular ring 75 to 100 metres in diameter, a noticeable variation in relation to the 500 to 3000 metres from turbines to impacted receptors.This paper relates factors identified previously by others to facts determined by recording and analyzing the differences in samples of sound over a full year at sites in a wind power development of 110 Vestas V82 turbines in Ontario's Bruce County, located acceptably to provincial regulators for spacing from wind turbines, and at control sites in the same environment at greater distances from the turbines. METHODSThis paper will identify key findings related to the subject of sound of wind turbines identified by others at the Fourth International Meeting on Wind Turbine Noise held in Rome, in April 2011, and the 161st Meeting of the American Acoustical Society, in Seattle, in May 2011.Then, this paper will outline how the research conducted in this study relates to the issues raised by others.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0030.000

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 head0.121
GPT teacher head0.360
Teacher spread0.240 · 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.

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
Published2011
Admission routes2
Has abstractyes

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