Assessment of the breeding value of Holstein black-and-white stud bulls in the Republic of Kazakhstan
Bibliographic record
Abstract
Currently, the dairy cow industry's primary goal is to reach maximum indicators in the manufacture of high-quality goods. It is necessary to utilize high-quality animals in breeding and productive qualities to attain this goal. Numerous research and practical works have proven that stud bulls have a major impact on the genetic effect of animal stock correction: proper stud bull selection ensures maximal genetic development in animal production. Animals of the Holstein breed of various selections are used to enhance domestic black-and-white cattle (Canadian, American, Danish, etc.). The article presents the results of the assessment of stud bulls according to the Instructions in force in the Republic of Kazakhstan. As an object of research, information was used on first-calvers (daughters) who lactated in 2016-2017 in the breeding herds of the republican populations of Holstein cattle. In a comparative aspect, the analysis of the results of a study of the breeding qualities of the estimated bulls in the context of different years and in total is carried out. The necessity of applying new approaches to assessing the breeding value of stud bulls in dairy cattle breeding is established.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".