СЕМЕНОВОДСТВО ЗЕРНОФУРАЖНЫХ КУЛЬТУР НА НАРЫМСКОЙ ГОСУДАРСТВЕННОЙ СЕЛЕКЦИОННОЙ СТАНЦИИ: ИСТОРИЧЕСКИЙ ОБЗОР
Bibliographic record
Abstract
There are presented the historical material on original seed production of grain-fodder crops at the Narym State Breeding Station, Tomsk Region. The material was prepared according to archive documents, reports of researchers for 1938-2014. The barley seed production work started in 1938, oats in 1939. In the thirties-forties of the XX century, the key task of seed production was to produce high-yielding elite seeds of high varietal purity, good sowing qualities, free from pests and diseases, which passed systemic directional selection and training in primary seed production network. The work towards improving the productive qualities of elite seeds of oats and barley was done by means of itravarietal hybridization, strict grading of lines against a high agricultural background, and selection of the most high-producing offspring. Since 1956, seed production has changed over to the method of individual-nepotistic selection. As a result of experiments has been found that the NPK-compound application to oats produces a significant increase in productivity. With the separate application of nitrogen, phosphorus and potassium, the significant increase in yield was obtained only from nitrogen. Beginning with 1973 and up to now, seed production produce only seeds of oat varieties bred at Narym: Narymskiy 943, Taezhnik, Metis, Togurchanin, Mustang. As a result of the work done, the original high-quality stock seeds are produced annually.
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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 | 0.002 |
| 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 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.008 |
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".