Phylogeny and synonymous codon usage pattern of <i>Papaya ringspot virus</i> coat protein gene in the sub-Himalayan region of north-east India
Bibliographic record
Abstract
Sub-Himalayan West Bengal is favorable for the production of several fruits and vegetables. Papaya is one of the common plants cultivated in the area. Most of the papaya plants of the area are susceptible to Papaya ringspot virus (PRSV). Coat protein genes of 6 PRSV isolates of the area were sequenced following RT-PCR. Phylogenetic study of the PRSV isolates showed about 80%-90% similarity with Cuban isolates. The codon usage pattern of our isolates was also analyzed, along with several other isolates. PRSV isolates of our study showed a preference for 8 putative optimal codons. Correspondence analysis of the genes of different isolates along the first 2 major axes were done, as the first 2 axes contributed more in shaping codon usage pattern. In the phylogenetic tree constructed by the neighbour-joining method, our isolates clustered together with the east Indian, north Indian, and Bangladeshi isolates. The diversity and codon usage pattern of the PRSV isolates of different regions were studied, and it was observed that the codon usage pattern of PRSV isolates is probably influenced by translational selection along with mutational bias.
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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 | 0.001 |
| 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".