MétaCan
Menu
Back to cohort
Record W2110093876 · doi:10.3354/meps09728

Population genetic structure in a deepwater fish Coryphaenoides rupestris: patterns and processes

2012· article· en· W2110093876 on OpenAlexaboutno aff
Halvor Knutsen, PE Jorde, Odd Aksel Bergstad, Morten D. Skogen

Bibliographic record

VenueMarine Ecology Progress Series · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDemersal zonePelagic zoneGenetic structureBiologyPopulationBiological dispersalGene flowDemersal fishEcologyRange (aeronautics)FisheryFishingGenetic variationDemography

Abstract

fetched live from OpenAlex

We observed significant genetic structure in a widely distributed North Atlantic demersal deepwater fish, the roundnose grenadier Coryphaenoides rupestris (Pisces: Macrouridae).The overall estimate of genetic differentiation, based on 6 microsatellite loci (F ST = 0.0152; p < 0.0001), was elevated by samples from the periphery of the species' range, off Norway and Canada.Samples from the central area of distribution showed less pronounced genetic structure, indicating more extensive dispersal and gene flow.Simulations were run to assess expected patterns of genetic differentiation under 2 major hypotheses of gene flow: passive larval drift and demographic diffusion.In spite of the relatively long duration of the pelagic egg and juvenile phases, no correlation was found between observed pairwise F ST values and those predicted under the hypothesis of drift of progeny by ocean currents.The observed pattern may instead arise from a combination of bathymetric barriers limiting deep pelagic mixing and advection, early life ontogenetic changes in vertical distribution, and limited migration once a benthopelagic life style has been established.

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 score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.005
GPT teacher head0.201
Teacher spread0.197 · 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

Citations29
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueMarine Ecology Progress SeriesSame topicFish Ecology and Management StudiesFrench-language works237,207