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Record W2071730595 · doi:10.1139/f00-199

Divergence of brown trout (<i>Salmo trutta</i>) within glacial refugia

2000· article· en· W2071730595 on OpenAlexvenueno aff
Núria Sanz, José‐Luis García‐Marín, Carles Plá

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsnot available
FundersNational Eye Institute
KeywordsSalmoBrown troutFish migrationEcologyPopulationGlacial periodRange (aeronautics)BiologyHabitatGenetic structurePleistoceneGenetic divergenceGeographyFisheryGenetic variationFish <Actinopterygii>Genetic diversity

Abstract

fetched live from OpenAlex

The Pleistocene glaciations produced a range of changes that affected the genetic population structure of fish species. Usually, studies focused on the population structure of species in postglacial recolonized areas and less attention was devoted to species differentiation within refuge areas. Allelic frequencies for 21 polymorphic protein-coding loci were compared among 25 collections within a northwestern Iberian glacial refuge of brown trout (Salmo trutta) using adjusted frequencies for nine populations to account for introgressions with exogenous hatchery fish. The high divergence observed (FST = 0.645) and geographical patterns of allelic variation are interpreted to reflect the existence of strong population structuring among native populations of this refuge. Four major geographic groups were defined within the region: (i) in the Tajo River, (ii) in the Duero River, (iii) in the Sil River, and (iv) among Cantabrian Sea flowing rivers including present anadromous populations. These gene pools have diverged genetically and ecologically in response to climatic oscillations. Anthropogenic effects on habitat and fish populations seriously compromise their future.

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 score0.013
Threshold uncertainty score0.026

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.013
GPT teacher head0.215
Teacher spread0.201 · 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

Citations41
Published2000
Admission routes1
Has abstractyes

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