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Record W2827830006 · doi:10.1098/rsbl.2018.0214

Evidence of sociality in the timing and location of foraging in a colonial seabird

2018· article· en· W2827830006 on OpenAlexfundno aff
Teri B. Jones, Samantha C. Patrick, John P. Y. Arnould, Marlenne A. Rodríguez‐Malagón, Melanie R. Wells, Jonathan A. Green

Bibliographic record

VenueBiology Letters · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaDeakin UniversityParks VictoriaHolsworth Wildlife Research Endowment
KeywordsForagingSocialityBiologySeabirdPredationEcologySocial animalPopulationOptimal foraging theoryZoologyDemography

Abstract

fetched live from OpenAlex

Social foraging behaviours, which range from cooperative hunting to local enhancement, can result in increased prey capture and access to information, which may significantly reduce time and energy costs of acquiring prey. In colonial species, it has been proposed that the colony itself may act as a site of social information transfer and group formation. However, conclusive evidence from empirical studies is lacking. In particular, most studies in colonial species have generally focussed on behaviours either at the colony or at foraging sites in isolation, and have failed to directly connect social associations at the colony to social foraging. In this study, we simultaneously tracked 85% of a population of Australasian gannets ( Morus serrator ) over multiple foraging trips, to study social associations at the colony and test whether these associations influence the location of foraging sites. We found that gannets positively associate with conspecifics while departing from the colony and that co-departing gannets have more similar initial foraging patches than individuals that did not associate at the colony. These results provide strong evidence for the theory that the colony may provide a source of information that influences foraging location.

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 score0.596
Threshold uncertainty score0.182

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 head0.084
GPT teacher head0.310
Teacher spread0.226 · 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

Citations38
Published2018
Admission routes1
Has abstractyes

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