MétaCan
Menu
Back to cohort
Record W4406422787 · doi:10.1121/10.0034710

An analysis of self-reported sleep disturbance from nighttime wind turbine noise suggests minimal effects but highlights the need for standardization in research design

2025· article· en· W4406422787 on OpenAlexaffabout
David S. Michaud, Mireille Guay, Stephen E. Keith, Allison Denning, James P. McNamee

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2025
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsHealth Canada
Fundersnot available
KeywordsStandardizationDisturbance (geology)Noise (video)TurbineSleep (system call)Sleep disorderComputer scienceEngineeringPsychologyArtificial intelligenceAerospace engineeringGeologyPsychiatryInsomnia

Abstract

fetched live from OpenAlex

The World Health Organization Environmental Noise Guidelines provide source-based nighttime sound level (Lnight) recommendations. For non-aircraft sources, the recommended Lnight is where the absolute prevalence of high sleep disturbance (HSD) equals 3%. The Guideline Development Group did not provide an Lnight for wind turbines due to inadequate data. In the current study, calculated outdoor wind turbine Lnight levels ranged from <20.5 to 41.5 dB(A). Between May and September 2013, questionnaires were completed by 606 males and 632 females, 18-79 years of age, randomly selected from households 0.25 to 11.22 km from operational wind turbines. When the source of sleep disturbance was unspecified, the mean prevalence of HSD was 13.3% overall and unrelated to Lnight (p = 0.53). As Lnight increased, identifying wind turbines as one of the causes of HSD increased from 0% below 20.5 dB(A) to 3.8% between 35.5-41.5 dB(A) (p = 0.01). The 3%HSD benchmark was observed where Lnight was 33.5 dB(A) [95% confidence interval (CI) 31.1-36.1 dB(A)]. Results affirm findings from Health Canada's Community Noise and Health Study of minimal impacts of wind turbines on sleep [Michaud et al. (2016a). "Effects of wind turbine noise on self-reported and objective measures of sleep," Sleep 39(1), 97-109], yet noted uncertainties and limitations are discussed, including the suggestion that the HSD benchmark for wind turbines may be too low.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.497
Threshold uncertainty score0.448

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.034
GPT teacher head0.393
Teacher spread0.360 · 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 designSimulation or modeling
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

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

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