Characterization of Novel Luteoviruses in Canadian Highbush Blueberries Using High-Throughput Sequencing
Bibliographic record
Abstract
The Fraser Valley of British Columbia, Canada is among the top ten blueberry producing regions globally. Viral diseases are established in the region and significantly reduce average yields. While testing for two viruses is routine, characterization of all the viruses present in the region is incomplete. We used high-throughput sequencing to obtain an unbiased overview of RNA viruses present in 97 plants collected across the region. In addition to known viruses, we identified four luteoviruses previously unidentified in the region. Two of them matched the blueberry virus L (BlVL) and blueberry virus M (BlVM). recently found in the USA, while the third constitutes a new major variant of BlVM (BlVM-2), and the fourth a new luteovirus, which we named blueberry virus N (BlVN). The genome sequences were ~5 kbp long and contained four open-reading frames similar to other luteoviruses. PCR screening revealed that these luteoviruses are widespread in the region, and that plants typically harbour more than one of these luteoviruses. While luteoviruses are typically vectored by aphids, they were also present in nursery stock, indicating that spread also occurs via vegetative propagation.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".