Metagenomic Nanopore Sequencing Versus Conventional Diagnosis for Identification of the Dieback Pathogens of Mango Trees
Bibliographic record
Abstract
Dieback is one of the most dangerous fungal diseases affecting mango trees. In this study, nanopore metagenome sequencing of the root-soil samples and infected plant tissues was conducted to identify the fungal pathogens present. Soil analysis of the infected mango trees showed the abundance of the Dikarya subkingdom (59%) including Lasiodiplodia theobromae (15%), Alternaria alternata (6%), Ceratocystis huliohia and Colletotrichum gloeosporioides. Analysis of the infected plant tissues revealed the presence of A. alternata (34%). The data were deposited in the National Center of Biotechnology Information (PRJNA767267). In conclusion, nanopore metagenome sequencing analysis was a valuable tool to rapidly identify dieback-associated fungal pathogens.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".