MétaCan
Menu
Back to cohort
Record W2227301701 · doi:10.1007/s00705-018-3723-z

Taxonomy of prokaryotic viruses: 2017 update from the ICTV Bacterial and Archaeal Viruses Subcommittee

2018· article· en· W2227301701 on OpenAlexaff
Evelien M. Adriaenssens, Johannes Wittmann, Jens H. Kuhn, Dann Turner, Matthew B. Sullivan, Bas E. Dutilh, Ho Bin Jang, Leonardo Joaquim van Zyl, Jochen Klumpp, Małgorzata Łobocka, Andrea I. Moreno‐Switt, J. Rumnieks, Robert A. Edwards, Jumpei Uchiyama, Poliane Alfenas‐Zerbini, Nicola K. Petty, Andrew M. Kropinski, Jakub Barylski, Annika Gillis, Martha R. J. Clokie, David Prangishvili, Rob Lavigne, Ramy K. Aziz, Siobain Duffy, Mart Krupovìč, Minna M. Poranen, Petar Knežević, François Enault, Yigang Tong, Hanna M. Oksanen, J. Rodney Brister

Bibliographic record

VenueArchives of Virology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversity of Guelph
FundersU.S. National Library of MedicineNational Institute of Allergy and Infectious DiseasesBattelleNederlandse Organisatie voor Wetenschappelijk OnderzoekFonds Wetenschappelijk OnderzoekVlaamse regeringFonds De La Recherche Scientifique - FNRSAcademy of FinlandUniversity of PittsburghHelsingin YliopistoNational Institutes of HealthU.S. Department of Health and Human ServicesNational Science Foundation
KeywordsBiologyVirus classificationVirologyTaxonomy (biology)Biological classificationComputational biologyEvolutionary biologyGeneticsGenomeZoologyGene

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.011
metaresearch head score (Gemma)0.020
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 score0.016
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0110.009
Science and technology studies0.0010.002
Scholarly communication0.0030.006
Open science0.0030.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.004

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 head0.025
GPT teacher head0.249
Teacher spread0.225 · 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

Citations267
Published2018
Admission routes1
Has abstractno

Explore more

Same venueArchives of VirologySame topicBacteriophages and microbial interactionsFrench-language works237,207