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Record W2107181946 · doi:10.1111/eth.12430

Ready to Fight: Reliable Predictors of Attack in a Cooperatively Breeding, Non‐Passerine Bird

2015· article· en· W2107181946 on OpenAlexafffund
Leanne A. Grieves, David M. Logue, Jim S Quinn

Bibliographic record

VenueEthology · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of LethbridgeMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAggressionComputer securityPasserinePoison controlCommunicationPsychologySocial psychologyZoologyBiologyComputer scienceMedicineMedical emergency

Abstract

fetched live from OpenAlex

Abstract Signal reliability is a major focus of animal communication research. Aggressive signals are ideal for measuring signal reliability because the signal referent – attack or no attack – can be measured unambiguously. Signals of aggressive intent occur at elevated rates in aggressive contexts, predict subsequent aggression by the signaler, and elicit appropriate responses from receivers. We tested the ‘predictive criterion’ in smooth‐billed anis, Crotophaga ani , by broadcasting one of two playback types (‘ahnee’ calls only or ‘ahnee + hoot’ calls), presenting a taxidermic mount, and observing the animals’ behavior. Based on the hypotheses that ‘hoot’ calls and ‘throat‐inflation’ displays signal aggressive intent, we predicted that they would be associated with attack, and that signaling rate would increase over the time period leading up to an attack. Indeed, both hoots and throat‐inflation displays reliably predicted attack. The second prediction, that signaling rate increases in the time leading up to attack, was strongly supported for throat‐inflation displays, which increased over the pre‐attack period in both treatments. Hoots increased over the pre‐attack period in ahnee playbacks but not in ahnee + hoot playbacks. Hierarchical signaling systems are characterized by early, less‐reliable predictors of attack, and later, more reliable predictors of attack. During both natural and simulated interactions, the more‐reliable throat‐inflation display tended to precede the less‐reliable hoot call, suggesting that this signaling system is not hierarchical. In a comparison of 11 putative signals of aggressive intent in birds, the throat‐inflation display had the second highest mutual information (reduction in uncertainty) among visual signals and non‐passerine signals while hoots had below‐average mutual information. Natural observations indicate that both hoots and throat‐inflation displays occur in the context of aggressive between‐group encounters, and hoots also occur during within‐group interactions. Throat‐inflation displays appear to be reliable indicators of aggressive intent, but the function of hoot calls is less clear.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.521
Threshold uncertainty score0.120

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 head0.083
GPT teacher head0.308
Teacher spread0.225 · 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

Citations3
Published2015
Admission routes2
Has abstractyes

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