STUDY OF SOWING QUALITIES OF SOYBEAN SEEDS IN SEED FARMS OF AMUR REGION
Bibliographic record
Abstract
An analysis of soybean seeds prepared for sowing in the farms of the Tambov, Konstantinovsky and Ivanovo districts of the Amur Region was carried out. In the farms of the surveyed areas, in the structure of sown areas, the main soybean crop is cultivated, which constitutes a share in the structure of crop rotation of more than 70 %. For sowing, 9 varieties of soybean are prepared by the Soybean Institute and 2 varieties of breeding in Canada and Ukraine. Of the 9 varieties, 7 belong to medium ripe and 2 varieties to late ripe groups. The area of soybean sowing in the region is 70 % occupied by the breeding varieties of the Soybean Institute. The quality of the tested seeds of 9 soy varieties is not at the proper level. Of the 27 seed lots tested, 9 varieties of 10 lots (37%) belong to the second category (according to the purpose, these seeds of the second and third reproductions sown on seed plots of seed farms). Weather conditions in 2020 unfavorably developed on the quality of soybean grain harvesting. To improve the situation under the sowing of 2021, in the whole region, the share of elite soybean seeds, the production of the Soybean Institute, increased 1.8 times.
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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 | 0.001 |
| 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) | 0.001 | 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".