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Record W2107900324 · doi:10.1139/f05-094

Population genetic structure and postglacial colonization of Atlantic salmon (<i>Salmo salar</i>) in the Baltic Sea area based on microsatellite DNA variation

2005· article· en· W2107900324 on OpenAlexvenueno aff
Marjatta Säisä, Marja‐Liisa Koljonen, Riho Gross, Jan Nilsson, Jaana Tähtinen, Jarmo Koskiniemi, Anti Vasemägi

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsnot available
Fundersnot available
KeywordsSalmoRefugium (fishkeeping)PopulationGenetic structureFish migrationColonizationGeographyEcologyPhylogeographyGenetic diversityFisheryBiology

Abstract

fetched live from OpenAlex

The genetic structure and phylogeography of Atlantic salmon (Salmo salar) across the Baltic Sea basin and neighbouring areas (eastern Atlantic Ocean, North Sea, Barents Sea, White Sea, and two Russian lakes, Onega and Ladoga) were studied to resolve the partly contradictory hypotheses of the species' postglacial colonization history. Thirty-eight populations (total of 2180 individuals) were studied for nine DNA microsatellite loci. Within the Baltic Sea, the anadromous populations formed three clear groups, corresponding to the northern (Gulf of Bothnia), eastern (Gulf of Finland and eastern Baltic Main Basin), and southern regions (western Baltic Main Basin). The genetic differences among these three groups were clearly greater (G GB 5.6%; G GB being the proportion of diversity components between regions within basins) than were those among population groups in the eastern Atlantic Ocean (G GB 2.2%) from Ireland to the White Sea. The isolation-by-distance model explained part of the differentiation within, but not between, the regions. The results strongly indicate colonization of the Baltic Sea by at least three glacial lineages. Potential refugium areas for each lineage are proposed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.009
GPT teacher head0.203
Teacher spread0.194 · 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

Citations90
Published2005
Admission routes1
Has abstractyes

Explore more

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