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Record W2138636137 · doi:10.1098/rspb.2011.0884

Feather corticosterone of a nestling seabird reveals consequences of sex-specific parental investment

2011· article· en· W2138636137 on OpenAlexaff
Graham D. Fairhurst, Joan Navarro, Jacob González‐Solís, Tracy A. Marchant, Gary R. Bortolotti

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCorticosteroneOffspringForagingBiologySeabirdParental investmentFeatherPaternal careZoologySex allocationInvestment (military)EcologyHormoneEndocrinologyPredationPregnancyGenetics

Abstract

fetched live from OpenAlex

Offspring of long-lived species should face costs of parental trade-offs that vary with overall energetic demands encountered by parents during breeding. If sex differences exist in how parents make the trade-off, sex-specific differences may exist in the contribution of each parent to those costs. Adaptations of offspring facing such costs are not well understood, but the hormone corticosterone probably plays a role. We manipulated breeding effort in Cory's shearwaters (Calonectris diomedea) to increase costs to offspring and used an integrated measure of corticosterone from chick feathers to investigate how experimental variation in parental investment influences offspring physiology. Average foraging trip duration and foraging efficiency (FE) of breeding pairs were not related to chick corticosterone, but sex biases in FE were. Adult male investment was more strongly related to chick corticosterone than was female investment. Importantly, we show for the first time suppression of adrenocortical activity in nestling Procellariiform seabirds, and explain how our results indicate an adaptive mechanism invoked by chicks facing increased costs of parental trade-offs.

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 score0.279
Threshold uncertainty score0.896

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 studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.087
GPT teacher head0.245
Teacher spread0.158 · 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

Citations48
Published2011
Admission routes1
Has abstractyes

Explore more

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