MétaCan
Menu
Back to cohort
Record W2993501644 · doi:10.1007/s00705-019-04477-6

Binomial nomenclature for virus species: a consultation

2019· article· en· W2993501644 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueArchives of Virology · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsUniversity of Guelph
FundersNational Research, Development and Innovation OfficeBiotechnology and Biological Sciences Research CouncilMedical Research CouncilNational Institute of Allergy and Infectious DiseasesMississippi Agricultural and Forestry Experiment Station, Mississippi State UniversityNederlandse Organisatie voor Wetenschappelijk OnderzoekDepartment for Environment, Food and Rural Affairs, UK Government
KeywordsNomenclatureBiologyVirus classificationExecutive committeeTaxonomy (biology)Executive summaryZoologyManagementBiotechnologyGenetics

Abstract

fetched live from OpenAlex

The Executive Committee of the International Committee on Taxonomy of Viruses (ICTV) recognizes the need for a standardized nomenclature for virus species. This article sets out the case for establishing a binomial nomenclature and presents the advantages and disadvantages of different naming formats. The Executive Committee understands that adopting a binomial system would have major practical consequences, and invites comments from the virology community before making any decisions to change the existing nomenclature. The Executive Committee will take account of these comments in deciding whether to approve a standardized binomial system at its next meeting in October 2020. Note that this system would relate only to the formal names of virus species and not to the names of viruses.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.901
Threshold uncertainty score0.195

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.244
Teacher spread0.223 · 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