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Record W3196992772 · doi:10.1111/mms.12867

Birth‐site habitat selection in gray seals <i>(<scp>Halichoerus grypus</scp>)</i>: Effects of maternal age and parity and association with offspring weaning mass

2021· article· en· W3196992772 on OpenAlexafffund
Sydney J. J. Allen, W. Don Bowen, Cornelia E. den Heyer

Bibliographic record

VenueMarine Mammal Science · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsBedford Institute of OceanographyDalhousie University
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsHabitatOffspringEcologyBiologyWeaningAnimal sciencePregnancy

Abstract

fetched live from OpenAlex

Abstract Selection of birth‐site habitat can have important effects on the reproductive success of females and the survival of offspring. We studied birth‐site habitat selection by gray seals ( Halichoerus grypus ) on Sable Island, Nova Scotia, and the associated effect on offspring body mass at weaning. We identified a mosaic of eight habitats using orthorectified imagery from a photographic aerial survey conducted in January 2016. The distribution of birth sites of 814 females in 2014–2016 compared to the available habitat in 2016 provided evidence for positive selection of habitats that were not subject to tidal influence or flooding. The habitat selected for parturition varied with both female age and parity. Younger and inexperienced females were more likely to pup in beach habitat, while older and more experienced females were more commonly found inland and on vegetated dunes. Longitudinal data from 540 females observed between 2006 and 2016 revealed moderate repeatability of birth‐site habitat selection ( r = 0.269, 95% CI [0.236–0.326]). Pups born in inland sand habitat that did not flood averaged 1.5 kg heavier (~2%) at weaning than those born on tidally influenced beach habitat. Overall, birth‐site habitat selection was associated with small effects on offspring body mass at weaning.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.005
GPT teacher head0.201
Teacher spread0.196 · 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

Citations8
Published2021
Admission routes2
Has abstractyes

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