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Record W2892586303 · doi:10.1111/jeu.12691

Revisions to the Classification, Nomenclature, and Diversity of Eukaryotes

2018· article· en· W2892586303 on OpenAlexafffund
Sina M. Adl, David Bass, Christopher E. Lane, Conrad L. Schoch, А. В. Смирнов, Sabine Agatha, Cédric Berney, Matthew W. Brown, Fabien Burki, Paco Cárdenas, Ivan Čepička, Ludmila Chistyakova, Javier del Campo, Micah Dunthorn, Bente Edvardsen, Yana Eglit, Laure Guillou, Vladimı́r Hampl, Aaron A. Heiss, Mona Hoppenrath, Timothy Y. James, Anna Karnkowska, Sergey A. Karpov, Eunsoo Kim, Martin Kolísko, Alexander Kudryavtsev, Daniel J. G. Lahr, Enrique Lara, Line Le Gall, Denis H. Lynn, David G. Mann, Ramón Massana, Edward A. D. Mitchell, Christine Morrow, Jong Soo Park, Jan Pawłowski, Martha J. Powell, Daniel J. Richter, Sonja Rueckert, Lora L. Shadwick, Satoshi Shimano, Frederick W. Spiegel, Guifré Torruella, Noha H. Youssef, Vasily V. Zlatogursky, Qianqian Zhang

Bibliographic record

VenueJournal of Eukaryotic Microbiology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtist diversity and phylogeny
Canadian institutionsUniversity of British ColumbiaDalhousie UniversityUniversity of GuelphUniversity of Saskatchewan
FundersU.S. National Library of MedicineNatural Environment Research CouncilUniversitat Pompeu FabraNatural Sciences and Engineering Research Council of CanadaSight Research UKNational Institutes of HealthHarvard UniversityInstitució Catalana de Recerca i Estudis AvançatsDalhousie UniversityRussian Foundation for Basic ResearchCentre National de la Recherche ScientifiqueEuropean Regional Development FundMinisterstvo Školství, Mládeže a TělovýchovyUniversity of Technology SydneyNational Institute of Allergy and Infectious DiseasesInstitut Français de Recherche pour l'Exploitation de la MerAgence Nationale de la RechercheGeneralitat de CatalunyaRadcliffe Institute for Advanced Study, Harvard UniversityNational Science FoundationScience for Life LaboratoryBoise State UniversityBiotechnology and Biological Sciences Research CouncilCS FundGordon and Betty Moore FoundationRussian Science FoundationRussell Sage Foundation
KeywordsBiologyCladeEnvironmental DNAMonophylyEvolutionary biologyPhylogenetic treeNomenclatureDNA barcodingTaxonomic rankEcologyPhylogenetic nomenclatureZoologyBiodiversityTaxonomy (biology)GeneticsGene

Abstract

fetched live from OpenAlex

This revision of the classification of eukaryotes follows that of Adl et al., 2012 [J. Euk. Microbiol. 59(5)] and retains an emphasis on protists. Changes since have improved the resolution of many nodes in phylogenetic analyses. For some clades even families are being clearly resolved. As we had predicted, environmental sampling in the intervening years has massively increased the genetic information at hand. Consequently, we have discovered novel clades, exciting new genera and uncovered a massive species level diversity beyond the morphological species descriptions. Several clades known from environmental samples only have now found their home. Sampling soils, deeper marine waters and the deep sea will continue to fill us with surprises. The main changes in this revision are the confirmation that eukaryotes form at least two domains, the loss of monophyly in the Excavata, robust support for the Haptista and Cryptista. We provide suggested primer sets for DNA sequences from environmental samples that are effective for each clade. We have provided a guide to trophic functional guilds in an appendix, to facilitate the interpretation of environmental samples, and a standardized taxonomic guide for East Asian users.

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)0.020
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.006
Science and technology studies0.0040.010
Scholarly communication0.0070.008
Open science0.0040.004
Research integrity0.0020.009
Insufficient payload (model declined to judge)0.0030.003

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 head0.018
GPT teacher head0.244
Teacher spread0.227 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations1,399
Published2018
Admission routes2
Has abstractyes

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