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Record W2333536219 · doi:10.1139/cjz-2013-0303

Diversity of early life-history traits in freshwater eels and the evolution of their oceanic migrations

2014· article· en· W2333536219 on OpenAlexvenueno aff
Mari Kuroki, Michael J. Miller, Katsumi Tsukamoto

Bibliographic record

VenueCanadian Journal of Zoology · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyTemperate climateMetamorphosisLarvaBiological dispersalRange (aeronautics)EcologyLatitudeLife history theorySubspeciesTropicsSubtropicsLife historyPopulationGeography

Abstract

fetched live from OpenAlex

Early life-history traits of all 19 anguillid eel species and subspecies were examined to help understand the evolutionary processes of their oceanic migrations in comparison with their migration distances and the geography of their species ranges. Tropical species were found to have fewer myomeres, greater body depths, higher growth rates, shorter larval durations, and smaller maximum larval sizes than temperate species. The relationships among larval characteristics such as growth rate, age at metamorphosis, and maximum larval size differed among tropical and temperate species and corresponded with the maximum latitudes of their species ranges. Temperate eel leptocephali with slow growth and large maximum size with slender bodies appear to be specialized for long migrations and dispersal over a wide range of distances to higher latitudes, while having flexible sizes of metamorphosis and recruitment. Tropical species with faster growth metamorphose earlier at a relatively fixed size, which would facilitate larval retention near their species ranges at low latitudes. Changes in the early life-history traits of tropical eels appear to have occurred during the evolution of longer migrations as they entered temperate regions.

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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.008
GPT teacher head0.157
Teacher spread0.149 · 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

Citations59
Published2014
Admission routes1
Has abstractyes

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