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Record W2044693744 · doi:10.1139/f05-198

How does the European eel (<i>Anguilla anguilla</i>) retain its population structure during its larval migration across the North Atlantic Ocean?

2006· article· en· W2044693744 on OpenAlexvenueno aff
Anthony J. Kettle, Keith Haines

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReproductive biology and impacts on aquatic species
Canadian institutionsnot available
FundersNatural Environment Research CouncilSight Research UK
KeywordsSargasso seaRange (aeronautics)FisheryOceanographyLarvaLatitudeAnguilla rostrataPopulationGeographyBiologyEcologyGeology

Abstract

fetched live from OpenAlex

A Lagrangian model is presented of the current-carried migration of the leptocephali (larvae) of the European eel (Anguilla anguilla) across the North Atlantic Ocean from the spawning area in the Sargasso Sea to the adult range in Europe and North Africa. The success of larvae in crossing the Atlantic Ocean and reaching particular latitude bins on the eastern side depended strongly on starting location in the Sargasso Sea and migration depth. In the model domain, silver eel spawners can develop strategies for spawning location and migration depth to preferentially target particular regions in the adult range. This observation may help to explain the presence of gradients in molecular markers in eel samples collected across Europe. Spawning in the period of late winter – spring maximizes the average food availability along the 2-year larval trajectory. The fastest transatlantic larval migration in the model is about 2 years, and the route to Europe takes most of the larvae past the east coast of North America in the first year. These model results are consistent with the hypothesis that the European and American eel (Anguilla rostrata) could separate themselves on different sides of the Atlantic Ocean on the basis of the different durations of their larval stages.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.078
Threshold uncertainty score0.937

Codex and Gemma teacher scores by category

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

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 head0.209
Teacher spread0.200 · 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

Citations113
Published2006
Admission routes1
Has abstractyes

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