The effectiveness of genomic analysis of the breeding value of bulls
Bibliographic record
Abstract
A study on the effectiveness of the genomic assessment of the breeding value of breeding bulls was conducted at JSC Udmurtskoe for Breeding Work. The object of the study was the bulls of the Holstein breed, which have the results of genomic evaluation carried out according to the methods of different countries (Canada, Russia). Bulls born in 2018-2019 were selected for analysis. The best, according to the results of the assessment according to the Canadian methodology, was the bull Chancellor 362351615 (estimate 2022 – milk yield +741 kg, the mass fraction of fat in milk +0.04%, protein +0.31%, revaluation 2024 – milk yield +563 kg, the mass fraction of fat in milk +0.01%, protein +0.30%). According to the results of the Russian assessment, the bull Lotus 6099 was the best in terms of a set of characteristics, its genomic forecast for milk yield was +640 kg, the mass fraction of fat in milk +0.27%, protein +0.07%. Comparing the actual productivity of the daughters of the evaluated breeding bulls with the genomic analysis, it can be noted that for most of the studied signs, it is the Russian forecast of breeding value that is confirmed.
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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 | 0.002 | 0.003 |
| 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 | 0.001 | 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".