ВЛИЯНИЕ КЛИМАТИЧЕСКИХ ФАКТОРОВ НА РАЗВИТИЕ И ФОРМИРОВАНИЕ ХОЗЯЙСТВЕННО ЦЕННЫХ ПРИЗНАКОВ ОВСА
Bibliographic record
Abstract
The yields and main agronomic characters of oat varieties bred at the Narym State Breeding Station (since 2006, the Narym Department of the Siberian Research Institute of Agriculture and Peat) were analyzed to determine ones most adaptable to local conditions. Results revealed that air temperature and precipitation have a complex impact on the development and formation of economic traits in oats. As to the duration of the growing season, the varieties studied are related to four maturity groups: early ripening (Tayozhnik), medium-early (Metis, Megion, Mustang), mid-ripening (Narymsky, Togurchanin), and medium-late (Talisman). Warmth deficit and excess rainfall increased the length of the growing period, especially in the second half of the vegetation season. Excess rainfall reduces resistance of oats to lodging. Oats productivity increases, when weather conditions are close to the long-term norm. The highly productive varieties are Talisman and Togurchanin (4.21-4.01 t/ha), less productive one is Narymsky 943 (3.40 t/ha). As to grain size, Narymsky 943 is a leader: its average thousand-kernel weight has made up 40.2 g. Talisman variety has the smallest grain of 36.7 g. Oats generates high chaff under unfavorable conditions of warm and moisture availability. All the varieties studied, except Narymsky 943, are low chaffy, and are proved to be valuable as to grain quality.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".