PSX-10 Genome-wide association studies for clinical mastitis in dairy cattle
Bibliographic record
Abstract
Abstract Mastitis, the inflammation of the mammary gland caused by both gram-positive and gram-negative bacteria, causes the global dairy industry over $20 billion annually in losses due to changes in milk yield and quality. The goal of this study was to identify genetic variants, genes, and biological pathways that are associated with mastitis. We performed genome-wide association studies (GWAS) on 1,858 cows from two lactations with both medium (n = 87,493) and high density (n = 624,300) single nucleotide polymorphisms (SNP) using a single SNP mixed linear model implemented in GCTA software. A total of 288 SNPs across all evaluated models passed the 5% genome-wise false discovery rate threshold across all autosomes with emphasis on chromosomes 3, 14, 16, 12, 6, and 2. These SNPs were mapped to their corresponding genes using the bovine genome. Gene enrichment analysis was then performed to identify significant biological pathways associated with mastitis. The current study identified potential genes that are involved in the MAPK, C5a, and ion binding pathways, which have been previously associated with immune function and inflammation. Further validation and investigation are required to confirm the identified genes and pathways before implementation in breeding programs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".