Bibliographic record
Abstract
Abstract A survey of fig viruses was conducted from 2010 to 2012 on individual fig trees from outdoor gardens showing different symptoms associated with fig mosaic disease. A total of 30 fig leaf samples were collected from eight different provinces of mainland Spain and tested by reverse transcription polymerase chain reaction (RT‐PCR) to assess the presence of fig mosaic virus (FMV), fig leaf mottle‐associated virus 1 (FLMaV‐1), fig leaf mottle‐associated virus 2 (FLMaV‐2), fig mild mottle‐associated virus (FMMaV), fig latent virus 1 (FLV‐1) and Fig fleck‐associated virus (FFkaV). The 96.7% (29 samples of 30) of the analysed samples were infected with FMV, 16.7% (5 of 30) with FLMaV‐1 and 26.7% (8 of 30) with FMMaV, whereas all samples were negative for FLMaV‐2, FLV‐1 and FFkaV. Mixed infection was observed in 13 samples. Sequencing analyses results showed that FMV, FMMaV and FLMaV‐1 Spanish isolates shared 89–93% nt identity with other Mediterranean isolates of the same viruses. Phylogenetic analyses of the amplified RdRp fragment from the FMV grouped the Spanish isolates into a subgroup together with Japanese, Canadian and some Serbian and Turkish isolates. To our knowledge, this is the first report of FMV, FMMaV and FLMaV‐1 occurring in mainland Spain.
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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 | 0.001 | 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".