Identification, Characterization, and Molecular Detection of <i>Alfalfa mosaic virus</i> in Potato
Bibliographic record
Abstract
ABSTRACT Alfalfa mosaic virus (AMV) was detected in potato fields in several provinces in Canada and characterized by bioassay, enzyme-linked immunosorbent assay, and reverse-transcription polymerase chain reaction (RT-PCR). The identity of eight Canadian potato AMV isolates was confirmed by sequence analysis of their coat protein (CP) gene. Sequence and phylogenetic analysis indicated that these eight AMV potato isolates fell into one strain group, whereas a slight difference between Ca175 and the other Canadian AMV isolates was revealed. The Canadian AMV isolates, except Ca175, clustered together among other strains based on alignment of the CP gene sequence. To detect the virus, a pair of primers, AMV-F and AMV-R, specific to the AMV CP gene, was designed based on the nucleotide sequence alignment of known AMV strains. Evaluations showed that RT-PCR using this primer set was specific and sensitive for detecting AMV in potato leaf and tuber samples. AMV RNAs were easily detected in composite samples of 400 to 800 potato leaves or 200 to 400 tubers. Restriction analysis of PCR amplicons with SacI was a simple method for the confirmation of PCR tests. Thus, RT-PCR followed by restriction fragment length polymorphism analysis may be a useful approach for screening potato samples on a large scale for the presence of AMV.
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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 | 0.001 | 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) | 0.000 | 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".