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Record W1917315187 · doi:10.1002/wsb.546

Disentangling effects of noise from presence of anthropogenic infrastructure: Design and testing of system for large‐scale playback experiments

2015· article· en· W1917315187 on OpenAlexafffundabout
Patrícia Rosa, Colin R. Swider, Lionel Leston, Nicola Koper

Bibliographic record

VenueWildlife Society Bulletin · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCenovus Energy
KeywordsNoise (video)Environmental scienceWildlifeScale (ratio)AttenuationComputer scienceEnvironmental resource managementRemote sensingGeologyEcologyGeography

Abstract

fetched live from OpenAlex

ABSTRACT Anthropogenic noise may be detrimental to many bird species, and manipulative experiments would help us understand these effects. We present the design and validation of a self‐sustaining solar‐powered broadcasting system that will allow researchers to disentangle acute or chronic effects of noise from effects of the presence of infrastructure, even in remote areas. We tested the broadcasting system using a case study on noise from oil well infrastructure in southern Alberta, Canada. Recordings from 2 types of oil wells were obtained and then broadcasted through 6 independent playback units continuously for a period of 3 months in 2013, at sites undisturbed by oil development. Sound measurements at real oil wells and at sites with broadcasting systems simulating the noise from these oil wells demonstrated that real and projected noise had very similar sound pressure levels, attenuation trends, and spectral composition. Throughout this long‐term playback experiment, the system produced power and noise reliably and consistently. In conjunction with bird surveys, this experimental design and infrastructure can be used to allow researchers to dissociate the presence of anthropogenic development from associated noise, providing us with information that will help decrease the environmental impacts of human activities. © 2015 The Wildlife Society.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.394

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.026
GPT teacher head0.282
Teacher spread0.255 · 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 designBench or experimental
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

Citations12
Published2015
Admission routes3
Has abstractyes

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