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Record W3074396089 · doi:10.1007/s00705-020-04752-x

Changes to virus taxonomy and the Statutes ratified by the International Committee on Taxonomy of Viruses (2020)

2020· article· en· W3074396089 on OpenAlexaff
Peter J. Walker, Stuart G. Siddell, Elliot J. Lefkowitz, Arcady Mushegian, Evelien M. Adriaenssens, Donald M. Dempsey, Bas E. Dutilh, Balázs Harrach, Robert L. Harrison, R. Curtis Hendrickson, Sandra Junglen, Nick J. Knowles, Andrew M. Kropinski, Mart Krupovìč, Jens H. Kuhn, Max L. Nibert, Richard Orton, Luisa Rubino, Sead Sabanadzovic, Peter Simmonds, Donald B. Smith, Arvind Varsani, F. Murilo Zerbini, Andrew J. Davison

Bibliographic record

VenueArchives of Virology · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsUniversity of Guelph
FundersNational Research, Development and Innovation OfficeEuropean Research CouncilDirectorate for Biological SciencesNational Institute of Food and AgricultureNational Institute of Allergy and Infectious DiseasesMedical Research CouncilMississippi Agricultural and Forestry Experiment Station, Mississippi State UniversityBiotechnology and Biological Sciences Research CouncilNemzeti Kutatási Fejlesztési és Innovációs HivatalNederlandse Organisatie voor Wetenschappelijk OnderzoekCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorMaine Agricultural and Forest Experiment StationBundesministerium für Bildung und ForschungMississippi State UniversityU.S. Department of Agriculture
KeywordsVirus classificationStatuteTaxonomy (biology)BiologyVirologyPolitical scienceLawGenomeGeneticsZoologyGene

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)0.048
metaresearch head score (Gemma)0.080
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.108
Threshold uncertainty score0.255

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.080
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0070.005
Science and technology studies0.0050.004
Scholarly communication0.0080.003
Open science0.0050.003
Research integrity0.0220.021
Insufficient payload (model declined to judge)0.0040.004

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 head0.064
GPT teacher head0.252
Teacher spread0.188 · 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
GenreOther

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

Citations340
Published2020
Admission routes1
Has abstractno

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