Relationship between Symptoms Expression and Virus Detection in Cassava Brown Virus Streak-Infected Plants
Bibliographic record
Abstract
Diagnosis of Cassava brown streak disease (CBSD) has for long been based on foliar and root symptoms expression on infected plants. Variability in patterns of symptoms expression between varieties and seasons however, has meant that symptom-based diagnostics are unreliable. The current study established the relationship between symptom expression on cassava plants and the infection with Cassava brown streak virus (CBSV) using RT-PCR diagnostic tool. It was established that manifestation of CBSD-like symptoms (particularly the foliar chloroses and necrotic blotches) may not be an absolute indication of CBSV-infection. Only 67% of tested samples were both foliarly symptomatic and infected by the virus. About 22% of samples were free from CBSV despite being foliarly symptomatic and 7% were CBSV-infected but foliarly symptom less. Some CBSV-infected plants did not exhibit any foliar symptoms although had root necroses. A few CBSV-free plants were regenerated from infected cuttings in one of the four tested cultivars, Albert. Five out of fifteen (33%) plants cv. Albert were symptom less and two out of the five (40%) were CBSV-free. The findings from this study suggest that symptoms-based diagnosing for CBSV infections is unreliable. As some of CBSV-infected plants tend to be considered CBSV-free due to lack of the disease symptoms, the scenario might have contributed to unlimited spread of CBSD through latently-infected planting materials.
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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) | 0.000 | 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 | 0.001 |
| 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".