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Record W1983701440 · doi:10.1139/z05-021

Blubber fatty acids of gray seals reveal sex differences in the diet of a size-dimorphic marine carnivore

2005· article· en· W1983701440 on OpenAlexfundvenueno aff
Carrie A. Beck, Sara J. Iverson, W. Don Bowen

Bibliographic record

VenueCanadian Journal of Zoology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSexual dimorphismBiologyForagingPredationBlubberCarnivoreZoologyPredatorJuvenileEcology

Abstract

fetched live from OpenAlex

Sex differences in foraging behaviour have been attributed to size dimorphism, niche divergence, and sex-specific fitness-maximizing strategies. Although sex differences in diving behaviour of marine carnivores are thought to result in sex differences in diet, this is not known for any species over temporal scales relevant to life-history characteristics. We examined blubber fatty acid (FA) profiles of gray seals, Halichoerus grypus (Fabricius, 1791), a sexually size-dimorphic species in which sex differences in foraging behaviour have been observed. FA profiles reflect prey consumed over a period of weeks or months. FA profiles of adult males and females varied significantly by season but there was a season by sex interaction, indicating that seasonal changes in diet differed by sex. FA profiles of adults also varied interannually, with a significant sex by year interaction. Interannual variability may have been a response to changes in ocean-bottom temperatures affecting prey availability or changes in prey abundance. Adult FA profiles differed from those of 6-month-old juveniles; however, there was no evidence of sex differences in the diet of younger animals. Our results indicate that sex differences in the foraging behaviour of adults are reflected in differences in diet at multiple temporal scales.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.017
GPT teacher head0.220
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), 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

Citations60
Published2005
Admission routes2
Has abstractyes

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