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Phylogeography of Ponto‐Caspian crustaceans: a benthic–planktonic comparison

2003· article· en· W1966132906 on OpenAlexaff
Melania E. Cristescu, Paul D. N. Hebert, Teodora M. Onciu

Bibliographic record

VenueMolecular Ecology · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and environmental studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBiologyPhylogeographyBenthic zonePlanktonEcologyCrustaceanMonophylyTaxonFaunaZoologyCladePhylogenetics

Abstract

fetched live from OpenAlex

The Black, Azov, Caspian and Aral Seas, remnants of the intracontinental Paratethys basin, are home to a spectacular diversity of crustaceans. This study examines the past history of the Ponto-Caspian fauna through comparative phylogeographical studies on both benthic and planktonic taxa, based on an examination of nucleotide diversity in the mitochondrial, cytochrome c oxidase subunit 1 (COI) gene. The COI data reveal a striking example of phylogeographical concordance. All species analysed, three amphipods and three cladocerans, are characterized by two monophyletic clades corresponding to the Black and Caspian regions. However, this phylogeographical partition is, on average, four times deeper for the benthic amphipods than for the planktonic cladocerans. Based on standard molecular clocks, the Black and Caspian lineages of benthic crustaceans diverged at varied intervals from 1 to 8 million years ago. By contrast, planktonic lineages are more recent with their divergence occurring in the last million years. Levels of intraspecific polymorphisms are variable and generally lower in planktonic than benthic taxa. The mechanisms responsible for the high diversity of crustaceans in the Ponto-Caspian region are discussed on the basis of these results.

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 score0.012
Threshold uncertainty score0.024

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)0.0020.000

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 head0.200
Teacher spread0.192 · 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

Citations73
Published2003
Admission routes1
Has abstractyes

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