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Record W2148144759 · doi:10.1093/beheco/ars215

Multiple achromatic plumage ornaments signal to multiple receivers

2012· article· en· W2148144759 on OpenAlexaff
Sarah Guindre‐Parker, H. Grant Gilchrist, Sarah Baldo, Stéphanie M. Doucet, Oliver P. Love

Bibliographic record

VenueBehavioral Ecology · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsCarleton UniversityEnvironment and Climate Change CanadaUniversity of Windsor
Fundersnot available
KeywordsPlumageOrnamentsBiologyPasserineSexual selectionZoologyMate choiceAchromatic lensEcologyEvolutionary biologyCourtshipMatingGeographyOptics

Abstract

fetched live from OpenAlex

We investigated whether achromatic plumage traits can act as multiple ornaments in an Arctic-breeding passerine, the snow bunting (Plectrophenax nivalis). Specifically, we examine whether multiple ornaments are providing multiple differing messages, are redundant, are unreliable signals of male quality, or are aimed at different receivers. We measured plumage reflectance and pigmentation patterns made conspicuous during male inter- and intrasexual displays that advertise different plumage regions. Our results indicate that although several aspects of male plumage may have redundant messages, different body regions appear aimed at different receivers. The wings of males—displayed primarily toward females during courtship—appear to indicate a pair’s future reproductive performance. Conversely, melanin-based plumage reflectance displayed during intrasexual threat displays provides information on territory features and a male’s capacity to defend it (i.e., territory size, territory quality, testosterone levels). Taken together, we suggest that snow buntings have multiple ornaments that provide information of differential importance in inter- versus intrasexual communication. This study demonstrates that achromatic plumage traits can serve in complex communication.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score1.000

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)0.0020.001

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 head0.049
GPT teacher head0.274
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; both teacher heads agree on what is shown here.

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

Citations34
Published2012
Admission routes1
Has abstractyes

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