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Record W2172295949 · doi:10.1093/beheco/arm161

Does ambient noise affect growth and begging call structure in nestling birds?

2008· article· en· W2172295949 on OpenAlexaff
Marty L. Leonard, Andrew G. Horn

Bibliographic record

VenueBehavioral Ecology · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsDalhousie University
Fundersnot available
KeywordsBeggingBiologyNoise (video)Affect (linguistics)Ambient noise levelZoologyEcologyAcousticsSound (geography)CommunicationPsychologyPhysics

Abstract

fetched live from OpenAlex

Much of the research examining the effects of ambient noise on communication has focused on adult birds using acoustic signals in mate attraction and territory defense. Here, we examine the effects of noise exposure on young birds, which use acoustic signals to solicit food from parents. We found that nestling tree swallows (Tachycineta bicolor) exposed to playbacks of white noise, within natural amplitude levels, from days 3 to 15 posthatch had begging calls with higher minimum frequencies and narrower frequency ranges than control nestlings raised in nests without added noise. Differences in begging call structure also persisted in the absence of noise. Two days after the noise was removed, experimental nestlings produced calls that were narrower in frequency range and less complex than control nestlings. We found no difference in growth between experimental and control nestlings. Our results suggest that long-term noise exposure affects the structure of nestling begging calls. These effects persist in the absence of noise, suggesting that noise may affect how calls develop.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.022
GPT teacher head0.294
Teacher spread0.272 · 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 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

Citations87
Published2008
Admission routes1
Has abstractyes

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