Sequencing and analysis of the complete genome of the Russian cherry virus A isolate
Bibliographic record
Abstract
Virus diseases of stone fruit crops (Prunus spp.) reduce both fruit yield and quality and shorten the productive life of fruit trees. Of the more than fifty known viruses affecting these crops, cherry virus A (CVA, genus Capillovirus, family Betaflexiviridae) is one of the most common. During a survey of stone fruit collections of the Tsitsin Main Botanical Garden of the Russian Academy of Sciences (Moscow), a sweet cherry (P. avium) tree of the cultivar Iput with viruslike rugosity symptoms on the leaves was found. When studying the virome of this plant using high-throughput sequencing, reads related to CVA were obtained and the complete genome of a new isolate of this virus, named SwC14, was assembled. Typically of capilloviruses, the SwC14 genome contained two open reading frames encoding a viral replicase, a coat protein and a movement protein. The SwC14 genome sequence was shown to be closest to the genomes of some Canadian sweet cherry CVA isolates (99.4% identity) and 81.4-95.0% identical to isolates of this virus from other stone fruit species and other regions of the world, including the previously characterized Crimean isolate PTC (82.0% identity). CVA was also detected in six of the seven other symptomless cherry cultivars examined by RT-PCR.This is the first report of a divergent CVA isolate in Central Russia, which expands information on the geographical distribution and genetic diversity of the virus.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".