Discovery of Negative-Sense RNA Viruses in Trees Infected with Apple Rubbery Wood Disease by Next-Generation Sequencing
Bibliographic record
Abstract
Apple rubbery wood is a disease of apple found around the world, often associated with Apple flat limb disease, and regulated in many countries. Despite its long history in apple cultivation, the disease's causal agent has remained elusive. In this study, next-generation sequencing (NGS) was used to identify and characterize several related novel viral agents from apple rubbery wood-infected plants, which have been named Apple rubbery wood virus (ARWV) 1 and 2. Additional specimens with apple rubbery wood disease tested positive by polymerase chain reaction with primers designed to ARWV 1 and 2 genomic RNA segments. In an NGS-based screening of over 100 Malus and 100 Prunus specimens from a collection of virus-infected trees, only one Malus specimen was found to be infected with ARWV not known to be infected with the disease, which strongly suggests that ARWV is not commonly found in Malus spp. or other fruit trees. The two viruses are most closely related to members of the order Bunyavirales. Three RNA segments (large, medium, and small) were characterized and the viruses likely represent a new genus under the family Phenuiviridae, with a suggested name of Rubodvirus (Rubbery wood 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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".