ИМПОРТ ПЛЕМЕННОГО КРУПНОГО РОГАТОГО СКОТА В РОССИИ
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
В статье представлен информационный материал племенного учета, регистрируемого во ВНИИплем за 2018 г., о завозе племенного крупного рогатого скота и семени быков-производителей из стран с высокоразвитым молочным скотоводством в Россию. После значительного снижения численности импортного поголовья в 2014 году, начиная с 2016 года, завоз стал увеличиваться и к 2018 году увеличился на 20%. Основными странами-экспортерами племенных животных были Канада, Германия, Дания, Нидерланды. Породный состав завезенного племенного крупного рогатого скота на территорию Российской Федерации в 2018 году представлен 12 породами. Наибольший удельный вес занимает голштинская порода (90%). Разведением данной породы занимались в 33 регионах РФ. Ввоз семени племенных быков за 2018 год составил почти 3,6 млн. спермодоз: в т. ч. 94% голштинской породы. The article is an information material of breeding records registered by VNIIplem for 2018 on the import of breeding cattle and seed of bulls from countries with highly developed dairy cattle breeding in Russia. After a significant reduction in the number of imported livestock in 2014, starting from 2016, the import began to increase and by 2018 increased by 20%. The main exporting countries of breeding animals were Canada, Germany, Denmark and Netherlands. The pedigree structure of the brought breeding cattle to the territory of the Russian Federation in 2018 is presented by 12 breeds. The largest share is Holstein breed (90%). Breeding of this breed was engaged in 33 regions of the Russian Federation. The importation of semen of breeding bulls in 2018 amounted to almost 3.6 million dozes: including 94% of Holstein.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.025 |
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 it