Attempts to Identify Cassava Brown Streak Virus in Western Democratic Republic of Congo
Bibliographic record
Abstract
Root necrosis similar to those of the cassava brown streak disease (CBSD) were observed on cassava in western provinces of the Democratic Republic of Congo (DR.Congo) in the early 2000’s. However molecular laboratory diagnosis were not able to detect any causative agent responsible for the attacks, hence, the disease related to these symptoms was named CBSD-like disease. In order to assess the distribution and the incidence of the CBSD-like disease, surveys were carried out in four western provinces, comprising, Kwango and Kwilu, Sud Ubangi, Kinshasa and Kongo Central. CBSD-like disease was observed in all surveyed provinces on the basis of root symptoms because foliar symptoms were different to those of the documented cases of CBSD in other parts of east Africa. CBSD-like disease incidence was high in Kongo Central and Sud Ubangi, exceeding an average of 50 %, but low in Kwango and Kwilu (32.8%) and in Kinshasa (19.1%). During the surveys, cassava leaf samples were collected for lab identification of the causal agent. PCR diagnosis was done on these samples using primers specific for the two known CBSVs. All samples tested negative with no amplification of DNA fragments of the correct size. Thus, further analysis on the causative organism is needed using Next Generation Sequencing (NGS) approaches. NGS approaches will help also to identify the causative organism in other Central Africa countries (Angola, Congo-Brazzaville and Gabon) where such cassava root necrosis have been reported or are suspected.
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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 | 0.001 |
| 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".