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Record W4411237020 · doi:10.1111/ibi.13420

Nest clustering correlates with breeding phenology rather than female relatedness in Red‐breasted Mergansers (<i>Mergus serrator</i>)

2025· article· en· W4411237020 on OpenAlexafffundabout
Geneviève M. Gauthier, Emily M. Burt, Rodger D. Titman, Natalie J. Thimot, Kyle W. Wellband, Kyle H. Elliott, Shawn R. Craik

Bibliographic record

VenueIbis · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversité LavalMcGill UniversityUniversité Sainte-Anne
FundersNatural Sciences and Engineering Research Council of CanadaFonds en Fiducie pour la Faune du Nouveau-BrunswickParks Canada
KeywordsNest (protein structural motif)PhenologyKestrelGeographyZoologyEcologyCluster analysisBiologyPredationStatistics

Abstract

fetched live from OpenAlex

Fine‐scale spatial and temporal genetic structuring of nests is possible in colonial birds that return to breed at their natal sites, and notably in waterfowl for which females are more philopatric than males. We genotyped female Red‐breasted Mergansers Mergus serrator breeding colonially on a coastal archipelago in eastern New Brunswick, Canada, during 2015 and calculated pairwise kinship coefficients using 4270 single nucleotide polymorphisms to assess whether related hens nest near each other and initiate their nests around the same time. We found no spatial or temporal genetic structure across islands; however, nesting was relatively synchronous between hens nesting close together. Red‐breasted Mergansers initiating their nests at the same time may select nearby nest‐sites based on the availability of dense vegetation that conceals nests, limiting opportunities for kin to nest near one another in this population.

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 categoriesInsufficient payload (model declined to judge)
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 score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.008
GPT teacher head0.219
Teacher spread0.211 · 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.

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

Citations0
Published2025
Admission routes3
Has abstractyes

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