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Record W2031319026 · doi:10.1094/phyto-05-13-0140-r

Viruses Associated with Rusty Mottle and Twisted Leaf Diseases of Sweet Cherry Are Distinct Species

2013· article· en· W2031319026 on OpenAlexfundno aff
D. E. V. Villamor, Kenneth C. Eastwell

Bibliographic record

VenuePhytopathology · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsnot available
FundersAgriculture and Agri-Food CanadaAnimal and Plant Health Inspection ServiceWashington State UniversityU.S. Department of Agriculture
KeywordsBiologyCladeMottlePhylogenetic treePlant virusVirologyBotanyVirusVirus classificationPrunusPotyvirusGeneticsGeneGenome

Abstract

fetched live from OpenAlex

Virus RNA sequences related to those of the family Betaflexiviridae were amplified from trees affected with the following diseases: cherry twisted leaf, apricot ring pox, cherry necrotic rusty mottle, cherry rusty mottle, and cherry green ring mottle. Phylogenetic analysis of virus sequences obtained from these diseased trees from western North America, along with published sequences of Cherry green ring mottle virus (CGRMV) and Cherry necrotic rusty mottle virus (CNRMV), revealed four major clades. Segregation into these four populations correlated with distinct symptom expression on woody indicators, suggesting that each clade represents a distinct virus species within the family Betaflexiviridae. The viruses occupying each clade were designated clade I: Cherry twisted leaf associated virus, clade II: CNRMV, clade III: Cherry rusty mottle associated virus, and clade IV: CGRMV. Potential recombination events were predicted to occur within and between these viruses, the latter being strongly supported by incongruent phylogenies. Examination of frequency distribution data derived from pairwise sequence comparisons of coat protein coding sequences resulted in a proposal for alternative guidelines for species demarcation for this family 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.

How this classification was reachedexpand

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.316

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 head0.043
GPT teacher head0.241
Teacher spread0.199 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations35
Published2013
Admission routes1
Has abstractyes

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