IMPROVEMENT OF BREEDING AND PRODUCTIVE QUALITIESOF THE ABERDEEN ANGUS BREED IN NORTHERN KAZAKHSTAN
Bibliographic record
Abstract
The article shows the findings of research material on the comparative characteristic of the growth and development of young Aberdeen Angus stock of different genotypes bred in the Northern Kazakhstan by Kolos LLP of Denisov district, Kostanay region. Male calve and heifer calves were evaluated for productive and breeding qualities. In this manuscript, it was established that the highest assessment scores, according to the research methodology, were observed in the young animals of Group I, which have genetic lineage connections to breeding stock (Canadian selection) and sired by the bull AAR Ten Gauge 1501 7AN425, known for its strong quantitative characteristics. The research results demonstrated that cows, as the Aberdeen Angus breeding stock, have high resistance to the transmission of offspring hereditary features. A middle position between peers is occupied by the following animals: group II (Estonian selection), according to the bull genotype AAA 17888695; III group (Kazakhstan selection) and according to the genotype of the bull KZP157796788. The trends identified in relation to traits that characterize the productive and breeding qualities of young Aberdeen Angus stock (young male calves and heifer calves) with various genotypes, suggest that the current livestock within the core farm can serve as replacements for breeding purposes and for achieving beef production.
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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".