Evaluation of Aberdeen Angus Breeding Bulls in the Northern Region of the Republic of Kazakhstan
Bibliographic record
Abstract
In this study, we evaluated the progeny quality of proven bulls of the Aberdeen Angus breed in different selections. Reliable information about the productive qualities of the daughters and cows of proven bulls is limited in Kazakhstan's scientific literature. We aimed to identify bull-improvers by comparatively evaluating cows of different genotypes in terms of productive qualities. The study was conducted in the period of 2021-2023, during which four groups of cows were formed based on origin. In conclusion, the high influence of inheritance of breeding features from bull-improvers should be highlighted: 78.6% to the daughters of cows of group I (Estonian selection from Kolos-firma LLP: EE 14465116 ABAJA PORTOS 95283, DK 1989501341 FREDERIK 95220, and EE 16966079 ABAJA PATRICK 95305) and 74.5% to the daughters of cows of group III (Canadian selection from Vishnevskoe LLP: BH BRUIN 54X 1644270 and JL DISTRICT 0311 1594050). There was less influence from proven bulls of deteriorators of the Kazakh selection: 21.4% to the daughters of cows of group II from Kolos-firma LLP (KZP156547191) and 25.5% to the daughters of cows of group IV from Vishnevskoe LLP (Henri KZT157789649 and Argus KZT155778964). Therefore, it is recommended that valuable genotypes of imported selection are used in breeding work in the Kostanay and North Kazakhstan regions for the improvement of Aberdeen Angus cattle.
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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 | 0.000 |
| 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".