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Comparison of Color and Body Condition Between Early and Late Breeding King Penguins

2008· article· en· W1993223864 on OpenAlexfundno aff
F. Stephen Dobson, Paul M. Nolan, Marion Nicolaus, Catherine Bajzak, Anne‐Sophie Coquel, Pierre Jouventin

Bibliographic record

VenueEthology · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsnot available
FundersInstitut Polaire Français Paul Emile VictorPolar Knowledge CanadaAuburn University
KeywordsBeakPlumageFeatherFledgeBiologySeasonal breederZoologyParusOrange (colour)OrnamentsEcologyHatchingGeographyHorticulture

Abstract

fetched live from OpenAlex

Abstract Early breeding is associated with greater reproductive success in many species. In king penguins, Aptenodytes patagonicus , laying extends for 6 mo. Early breeders may fledge a single chick at best, but late breeders virtually never fledge a chick. For early and late breeders, we compared colored ornaments known to be important in mate choice: yellow–orange feathers of the breast and auricular areas, and an ultraviolet and yellow–orange beak spot. Our purpose was to discern differences between males and females in this highly sexually monomorphic species, as well as to discern whether colored ornaments are more important for the more successful early breeders (aspects of color were hue, chroma, and brightness). For this, we weighed and measured 130 penguins. Early males had greater reflectance of ultraviolet color from the beak spot than did early females and late breeders of both sexes, and the early males were heavier and in better condition than late breeding males or females. Late breeding females were the yellowest in breast hue, a trait that has been linked to immunocompetence. Within pairs, males and females were significantly correlated in body mass, but only early in the breeding season. We concluded that early in the breeding season when reproductive success was greatest, potential mates were not only more similar in body mass, but also that females may have chosen males that had brighter beak spots and were in better body condition.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.399
Threshold uncertainty score0.125

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 head0.092
GPT teacher head0.330
Teacher spread0.238 · 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

Citations36
Published2008
Admission routes1
Has abstractyes

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