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Record W2954281990 · doi:10.1093/beheco/arz109

Behavioral, energetic, and color trait integration in male guppies: testing the melanocortin hypothesis

2019· article· en· W2954281990 on OpenAlexaff
Francesca Santostefano, Kerry V. Fanson, John A. Endler, Peter A. Biro

Bibliographic record

VenueBehavioral Ecology · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversité du Québec à Montréal
FundersAustralian Research Council
KeywordsBiologyBoldnessTraitGuppyCourtshipMelanocortinMate choiceBehavioral syndromePoeciliaDanioSexual selectionPopulationXiphophorusEcologyZoologyEvolutionary biologyZebrafishGeneticsFish <Actinopterygii>PersonalityGeneSocial psychologyPsychology

Abstract

fetched live from OpenAlex

Abstract Individuals of the same population differ consistently from each other in the average expression of behavioral and physiological traits. Often, such traits are integrated and thus correlated with each other. However, the underlying proximate mechanisms generating and maintaining this among-individual covariation are still poorly understood. The melanocortin hypothesis suggests that the melanocortin pathways can have pleiotropic effects linking the expression of melanin-based coloration with physiological and behavioral traits. In the present study, we test this hypothesis in adult male guppies (Poecilia reticulata), by estimating among individual correlations between behaviors (activity, feeding, boldness, display, and chase during courtship), stress response (peak metabolic rate), and coloration (black spot, fuzzy black, and orange). The lack of correlation of any behavior or metabolism with black coloration indicates that the melanocortin hypothesis is not supported in this species. However, we observed covariation among coloration traits, as well as among behavioral traits. Our findings suggest that, although there appear to be constraints within sets of related traits, coloration, physiology, and behaviors can potentially evolve as independent modules in response to selection in this species.

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 score0.611
Threshold uncertainty score0.975

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)0.0010.000

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 head0.064
GPT teacher head0.260
Teacher spread0.197 · 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

Citations17
Published2019
Admission routes1
Has abstractyes

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