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Record W3048916107 · doi:10.1111/ppa.13255

Facing <i>Rose rosette virus</i> : A risk to European rose cultivation

2020· article· en· W3048916107 on OpenAlexaboutno aff
Inés Vázquez-Iglesias, Francisco M. Ochoa‐Corona, Joe Tang, Rebekah J. Robinson, G. R. G. Clover, Adrian Fox, Neil Boonham

Bibliographic record

VenuePlant Pathology · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyRosette (schizont appearance)Rose (mathematics)Ornamental plantBroomPlant virusCut flowersHorticultureVeterinary medicineVirusVirologyEcology

Abstract

fetched live from OpenAlex

Abstract Roses ( Rosa ) are one of the most valuable ornamental flowering shrubs around the globe. They are susceptible to numerous pathogens that require management, increasing the cost of cultivation. Rose rosette virus (RRV; genus Emaravirus ) is a devastating virus that has been spreading since the 1940s in the United States and Canada. It is an emerging risk to European and worldwide rose cultivation, causing symptoms such as witches' broom, malformations, excessive thorn production, and eventually plant death. RRV is transmitted by the eriophyid mite Phyllocoptes fructiphilus and by grafting. Research is being undertaken to understand RRV and to find control measures and resistant cultivars, as they are not currently available. Early detection of the disease is the key to prevent the establishment and spread of RRV and its vector. Different molecular and serological diagnostic methods have been designed and implemented, including ELISA, RT‐PCR, RT‐qPCR, LAMP, and high‐throughput sequencing. RRV infected plants can remain symptomless for long periods, so these diagnostic assays are necessary in conjunction with visual assessment to facilitate early detection. Significant social, economic, and environmental impacts are expected if RRV and its vector establish and spread in Europe. Rose trade between countries is the most likely pathway of introduction of RRV into Europe. In this review we describe current knowledge about RRV, the molecular and serological methods available for the detection of this virus, pathways to entry, and the possible impact if it establishes and spreads in Europe.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.836
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.001

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 head0.046
GPT teacher head0.242
Teacher spread0.196 · 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.

Study designBench or experimental
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

Citations23
Published2020
Admission routes1
Has abstractyes

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