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Record W4306292889 · doi:10.1093/ve/veac100

Formal recognition and classification of gene transfer agents as viriforms

2022· article· en· W4306292889 on OpenAlexafffund
Roman Kogay, Sonja Koppenhöfer, Andrew S. Lang, Olga Zhaxybayeva

Bibliographic record

VenueVirus Evolution · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversity of British ColumbiaMemorial University of Newfoundland
FundersNational Institute of Allergy and Infectious DiseasesNatural Sciences and Engineering Research Council of CanadaSimons Foundation
KeywordsGene transferComputer scienceArtificial intelligencePattern recognition (psychology)Natural language processingGeneBiologyGenetics

Abstract

fetched live from OpenAlex

Morphological and genetic features strongly suggest that gene transfer agents (GTAs) are caudoviricete-derived entities that have evolved in concert with cellular genomes to such a degree that they should not be considered viruses. Indeed, GTA particles resemble caudoviricete virions, but, in contrast to caudoviricetes (or any viruses), GTAs can encapsidate at best only part of their own genomes, are induced solely in small subpopulations of prokaryotic host cells, and are transmitted vertically as part of cellular genomes during replication and division. Therefore, the lifecycles of GTAs are analogous to virus-derived entities found in the parasitoid wasps, which have recently been recognized as non-virus entities and therefore reclassified as viriforms. We evaluated three distinct, independently exapted GTA groups, for which the genetic basis for GTA particle production has been established. Based on the evidence, we outline a classification scheme for these viriforms.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.003
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.020
GPT teacher head0.272
Teacher spread0.253 · 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 designTheoretical or conceptual
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

Citations19
Published2022
Admission routes2
Has abstractyes

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