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Record W2858266604 · doi:10.1139/gen-2018-0043

Intraspecific mitogenomics of three marine species-at-risk: Atlantic, spotted, and northern wolffish (<i>Anarhichas</i> spp.)

2018· article· en· W2858266604 on OpenAlexaffvenue
Linda A. Lait, Steven M. Carr

Bibliographic record

VenueGenome · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsUniversity of GuelphMemorial University of Newfoundland
Fundersnot available
KeywordsBiologyPhylogeographyEcologyIntraspecific competitionGlacial periodGenetic structureSympatric speciationPopulationHaplogroupSpecies complexZoologyGenetic variationPhylogeneticsPhylogenetic tree

Abstract

fetched live from OpenAlex

High-resolution mitogenomics of within-species relationships can answer such phylogeographic questions as how species survived the most recent glaciation, as well as identify contemporary factors such as physical barriers, isolation, and gene flow. We examined the mitogenomic population structure of three at-risk species of wolffish: Atlantic (Anarhichas lupus), spotted (A. minor), and northern (A. denticulatus). These species are extensively sympatric across the North Atlantic but exhibit very different life history strategies, a combination that results in concordant and discordant patterns of genetic variation and structure. Wolffish haplogroups were not structured geographically: Atlantic and spotted wolffish each comprised three shallow clades, whereas northern wolffish comprised two deeper but unstructured lineages. We suggest that wolffish species survived in isolation in multiple glacial refugia, either refugia within refugia (Atlantic and spotted wolffish) or more distant refugia (northern wolffish), followed by secondary admixture upon post-glacial recolonisation of the North Atlantic.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

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 head0.010
GPT teacher head0.188
Teacher spread0.178 · 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

Citations6
Published2018
Admission routes2
Has abstractyes

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