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Record W2768483453 · doi:10.1093/jcbiol/rux076

Molecular phylogeny of the genus Themisto (Guérin, 1925) (Amphipoda: Hyperiidae) in the Northern Hemisphere

2017· article· en· W2768483453 on OpenAlexaff
Astrid Tempestini, Louis Fortier, Alexei I. Pinchuk, France Dufresne

Bibliographic record

VenueJournal of Crustacean Biology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsCenter for Northern StudiesUniversité LavalUniversité du Québec à Rimouski
Fundersnot available
KeywordsBiologyAmphipodaPhylogeneticsEcologyPhylogenetic treeEvolutionary biologyZoologyCrustaceanGeneticsGene

Abstract

fetched live from OpenAlex

The Amphipoda is a highly speciose order of crustaceans with a life cycle characterized by direct development and no larval stage, making them interesting models for studies on marine speciation. The family Hyperiidae Dana, 1852 is a strictly pelagic group of Amphipoda. In northern latitudes, free-swimming hyperiids belonging to the genus Themisto (Guérin, 1825) are important components of marine ecosystems in term of abundance and biomass, but little is known about their genetic relationships. We present the first multi-locus molecular phylogenetic assessment of the Themisto in the Northern Hemisphere. We performed Bayesian and maximum likelihood reconstructions based on three nuclear loci (18S rDNA, 28S rDNA, and Histone 3) and mitochondrial cytochrome oxidase I data on eight specimens of Themisto from the Pacific, Arctic, and Atlantic oceans. We also provide an updated molecular phylogeny of Hyperiidae. Based on our multi-locus phylogeny, we report the presence of cryptic species in the North Pacific. Our results are discussed in the light of marine speciation.

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)0.000
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.013
GPT teacher head0.250
Teacher spread0.237 · 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

Citations11
Published2017
Admission routes1
Has abstractyes

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