THE RESULTS OF THE RESEARCH OF THE COLLECTION NURSERY OF OILSEED FLAX IN THE CONDITIONS OF THE AGRICULTURAL EXPERIMENTAL STATION «ZARECHNOYE» LLP
Bibliographic record
Abstract
The article presents data on the most important indicators in the cultivation of oilseed flax, obtained during research at the Agricultural Experimental Station Zarechnoye LLP for 2022. The most intensive plant growth was observed after the flax plants passed the herringbone phase up to the flowering phase, the linear development of plants stopped. Intensive root growth in depth occurred in the early phases of development. During our research, flax plants have placed increased demands on heat, especially during the ripening period. At low air temperatures, the germination of seeds and the emergence of seedlings were significantly slowed down. According to the results of the research, promising varieties were identified that exceed the indicators of the standard variety. 36 varieties were sown in the nursery of oilseed flax in 2022. All of them are part of the world collection, they belong to Russian, Canadian, Ukrainian, etc. breeding. The domestic selection is represented by 6 varieties: Kustanayskaya-5, Kazar, Kostanay 11, Ilyich, Slavyachil, Altyn. The zoned Kazar variety was taken as the standard, which was located every 5 varieties. In regions where oilseed flax is cultivated, fusarium wilt is the main predominant type of disease. Resistance to fusarium wilt was determined by counting plants after germination and before harvesting in the infected area. Such varieties as Isilkulsky, Kinelsky 2000, Ilyich, Slavyachil, Kazar, Osean, Triumph, Istok, Antares, Kustanaysky 5 turned out to be moderately stable.
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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 | 0.001 | 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".