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Record W3005613051 · doi:10.1111/eth.13015

Nestling tree swallows (<i>Tachycineta bicolor</i>) alter begging behaviour in response to odour of familiar adults, but not their nests

2020· article· en· W3005613051 on OpenAlexafffund
Ilsa A. Griebel, Russell D. Dawson

Bibliographic record

VenueEthology · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Northern British Columbia
FundersBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsBeggingBiologyNest (protein structural motif)ZoologyIntraspecific competitionEcologyPopulationNeophobiaDemography

Abstract

fetched live from OpenAlex

Abstract Communication using chemical cues is important for many taxa, including birds, but the use of olfaction for intraspecific communication has been investigated only recently in passerines and is understudied in nestlings. To address this knowledge gap, we explored whether nestling tree swallows ( Tachycineta bicolor ) would recognize and respond to chemical cues of conspecifics, specifically testing begging responses to familiar and unfamiliar nest and adult odours. For the nest odour experiment, nests were treated with either orange essential oil or distilled water to create scented and unscented (control) odour environments, respectively. For the adult odour experiment, adults attending the nestlings were considered “familiar adults” and adults attending a different brood in the population were considered “unfamiliar adults.” We found that begging responses of nestlings did not differ in response to orange oil odour or water, but nestlings begged significantly longer and more intensely in response to odours of a familiar than an unfamiliar adult, regardless of adult sex. This provides evidence that tree swallows use chemical cues to alter their behaviour and opens up many exciting avenues of future research.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.845
Threshold uncertainty score0.296

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.048
GPT teacher head0.263
Teacher spread0.215 · 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 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

Citations5
Published2020
Admission routes2
Has abstractyes

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