Genetic Diagnostics of FANC1BY Mutation in Representatives of the Holstein Breed and Its Crosses
Bibliographic record
Abstract
The article is devoted to the development and use of a method for diagnosing the source of Brachyspina Syndrome, or short spine, in the Holstein breed and its crossbreeds. Representatives of this breed are the most highly productive animals in the world for milk. The development of a diagnostic method for breed-specific hereditary carriers is an important task in dairy farming. In this regard, the authors have proposed a Patent and a Reagent Kit for the detection of normal FANC1TY and mutant FANC1BY alleles in the Holstein breed and its crossbreeds. The frequency of occurrence of genotypes formed by these alleles in different sex and age groups of animals in the Holstein breed and its high-blooded hybrids was studied. Historical data related to the founders, from whom the spread of the mutant FANC1BY allele within the Holstein breed itself and its crossis in the USA, Canada and Russia began, has presented. The development of a diagnostic method for the mutant FANC1BY allele will make it possible to stop spreading of the Brachyspina Syndrome source. The proposed method will make it possible, in the early stages, to form healthy groups of breeding animals (bulls, replacement bulls, bull-reproducing cows), thereby laying the foundation for creating a high-quality livestock in the regions where the Holstein breed and its numerous crossbreeds are bred. cattle, Holstein breed, crossis, genotype, FANC1BY mutation, allele, Brachyspina syndrome
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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 | 0.002 | 0.000 |
| 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".