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Record W3037378360 · doi:10.1590/1982-0224-2019-0109

Phylogenetic relationships of the neon tetras Paracheirodon spp. (Characiformes: Characidae: Stethaprioninae), including comments on Petitella georgiae and Hemigrammus bleheri

2020· article· en· W3037378360 on OpenAlexaff
Pedro Bittencourt, Valeria Nogueira Machado., B. Marshall, Tomas Hrbek, Izeni Pires Farias

Bibliographic record

VenueNeotropical Ichthyology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFish biology, ecology, and behavior
Canadian institutionsUniversity of British Columbia
FundersFundação de Amparo à Pesquisa do Estado do AmazonasConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsCharaciformesBiologyCharacidaeSister groupMonophylyZoologyGenusTaxonPhylogenetic treeEcologyCladeFish <Actinopterygii>Genetics

Abstract

fetched live from OpenAlex

ABSTRACT Neon tetras (Paracheirodon spp.) are three colorful characid species with a complicated taxonomic history, and relationships among the species are poorly known. Molecular data resolved the relationships among the three neon tetras, and strongly supported monophyly of the genus and its sister taxon relationship to Brittanichthys. Additionally, the sister-taxon relationship of the rummy-nose tetras Hemigrammus bleheri and Petitella georgiae was strongly supported by molecular and morphological data. Therefore, we propose to transfer the rummy-nose tetras H. bleheri and H. rhodostomus to the genus Petitella. Furthermore, Petitella georgiae is likely to be a species complex comprised of at least two species.

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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.051
GPT teacher head0.257
Teacher spread0.206 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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