Detection and identification of Bogia coconut syndrome phytoplasma from seed-associated tissues and seedlings of coconut (Cocos nucifera) and betel nut (Areca catechu)
Bibliographic record
Abstract
Evidence for seed transmission of phytoplasmas has grown in several pathosystems including coconut (Cocos nucifera). Bogia coconut syndrome (BCS) is a disease associated with the lethal yellowing syndrome associated with the presence of 'Candidatus Phytoplasma noviguineense' that affects coconut, betel nut (Areca catechu) and bananas (Musa spp.) in Papua New Guinea. Coconut and betel nut drupes were sampled from BCS-infected areas in Papua New Guinea, dissected, the extracted nucleic acid was used in polymerase chain reaction (PCR), and loop mediated isothermal amplification (LAMP) used to check for presence of phytoplasma DNA. In a second study, drupes of both plant species were collected from multiple field sites and grown in insect-proof cages. Leaf samples taken at 6 months were also tested with PCR and LAMP. The studies of dissected coconut drupes detected phytoplasma DNA in several tissues including the embryo. Drupes from betel nut tested negative. Among the seedlings, evidence of possible seed transmission was found in both plant species. The results demonstrate the presence of 'Ca. P. noviguineense' in coconut drupes and seedlings, and in seedlings of betel nut; factors that need to be considered in ongoing management and containment efforts.
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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 | 0.000 | 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".