Влияние высоких температур на состояние древесных растений и их патогенов в защитных насаждениях Нижнего Поволжья
Bibliographic record
Abstract
The studies were carried out in 2014 (dry year) in protective stands of different purpose and design, and in the greeneries of the Volgograd region. The analysis for thermal stability of woody plants is carried out on the basis of the analysis of the range of structural changes for the crowns of trees. It was determined that various tree species, used to establish protective forest stands, considerably differed from each other on drought resistance and thermal influence. European white birch, European wild apple, wild pear tree, Siberian pea shrub, and Common horse chestnut were the species to have suffered from the drought in 2014 most of all. Black locust, Norway maple, and Canadian maple are the species of mean stability to high temperatures. Siberian elm, Black poplar, English oak (pyramidical), European ash, and Green ash were found to be the most thermally stable species. Thus, it is desirable to plant them establishing the protective stands on the south-eastern part of Russia. Thermal injuries of woody plants in the stands provoke weakening of the trees and noncontagious diseases occurrence. Carcinous and vascular malformations are considered to be the most dangerous. In hot summers, number of powdery mildew, infectious mottling, and rots decreases.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".