Effect of temperature on <scp>G</scp>a<scp>RV</scp>6 accumulation and its fungal host, the conifer pathogen <i>Gremmeniella abietina</i>
Bibliographic record
Abstract
Summary Gremmeniella abietina RNA virus 6 (GaRV6) was studied within the European race of G. abietina. We examined 97 isolates originating from Canada, Czech Republic, Finland, Italy, Montenegro, Serbia, Spain, Switzerland, Turkey and the United States. According to direct specific quantitative reverse transcription PCR (qRT‐PCR) screening based on the RNA‐dependent RNA polymerase (RdRp) sequence, the virus was mostly present in Spain, but it was also found at a very low concentration in three isolates from Canada, Italy and Finland. To gain insight into the three‐way interaction among temperature, GaRV6 and G. abietina, we performed an in vitro experiment with eight Spanish isolates (four infected and four uninfected) with four repetitions each. We assessed the virus expression (accumulation) based on the quantity of RdRp‐encoding RNA by qRT‐PCR and the G. abietina growth rate at 5, 15 and 20°C. The presence of the virus had a significant negative effect on the G. abietina growth rate, which was also significantly influenced by the temperature. However, the temperature appeared not to clearly determine the virus accumulation, and the virus accumulation did not have any influence on the growth rate of the infected G. abietina isolates. Taken together, these results suggest that the role of this virus as a relevant factor with respect to the more thermophilic nature of the Spanish population of G. abietina may be ruled out.
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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 | 0.001 |
| 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".