ON THE ISSUE OF PRESERVATION, RESTORATION, AND UTILIZATION OF GENETIC DIVERSITY IN CATTLE BREEDS WITHIN THE TERRITORY OF THE RUSSIAN FEDERATION
Bibliographic record
Abstract
На территорию РФ с 2006 года по настоящее время осуществляется интенсивный завоз крупного рогатого скота в основном из Австрии, Великобритании, Германии, Нидерландов, Канады, Франции и США. Для скрещивания и чистопородного разведения использовано около 100 отечественных и зарубежных пород. Отрасль унаследовала богатое разнообразие пород и породных групп. Большая часть крупного рогатого скота молочного направления в современной России является помесным (95%) поголовьем с различной долей кровности по голштинской породе. На начало 2023 года по 8 породам 16 хозяйств имеют статус генофондных. Из 25 пробонитированных пород крупного рогатого скота молочного направления 16 отечественных, допущенных к использованию, находятся в неустойчивом состоянии, а некоторые — в критическом. From 2006 to the present time, cattle have been intensively imported into the Russian Federation, mainly from Austria, Great Britain, Germany, the Netherlands, Canada, France, and the USA. About 100 domestic and foreign breeds have been used for crossbreeding and purebred breeding. The industry has inherited a rich diversity of breeds and breed groups. Most of the dairy cattle in modern Russia are crossbred (95%) with varying proportions of Holstein blood. At the beginning of 2023, 16 farms had gene pool status for 8 breeds. Of the 25 approved breeds of dairy cattle, 16 domestic ones approved for use are in an unstable state, and some are in a critical state.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".