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Record W1505130203 · doi:10.1111/ibi.12294

No evidence of divergence at neutral genetic markers between the two morphologically different subspecies of the most numerous Arctic seabird

2015· article· en· W1505130203 on OpenAlexaff
Katarzyna Wojczulanis‐Jakubas, Adrianna Kilikowska, Jérôme Fort, Maria Gavrilo, Dariusz Jakubas, Vicki L. Friesen

Bibliographic record

VenueIbis · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsQueen's University
Fundersnot available
KeywordsSubspeciesBiologySeabirdEvolutionary biologyArcticMicrosatellitemtDNA control regionPopulationGene flowMitochondrial DNAZoologyGenetic divergenceEcologyGenetic variationGeneticsGeneGenotypeHaplotypeGenetic diversityAllele

Abstract

fetched live from OpenAlex

Identifying natural populations that might be considered separate units using morphology, genotype or both is important in understanding the process of speciation and for conservation. We examined the relationships between the only two subspecies of the most numerous Arctic seabird, the Little Auk Alle alle, using both morphological (wing and head‐bill lengths) and genetic data (482 base pairs of the mitochondrial control region and seven nuclear microsatellite loci). We found significant morphological differences between the subspecies, A. a. polaris being significantly larger than the nominate A. a. alle. However, we did not find the subspecies to be differentiated at either mitochondrial DNA or at microsatellite loci. Consequently, one evolutionary significant unit is proposed. The similarity of the two subspecies at neutral genetic markers may be due to contemporary gene flow between populations, as well as large population sizes both in the present and in the past, combined with recent post‐glacial colonization of the Artic.

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)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.256
Teacher spread0.220 · 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

Citations10
Published2015
Admission routes1
Has abstractyes

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