Genetic associations of ketosis and displaced abomasum with milk production traits in early first lactation of Canadian Holsteins
Bibliographic record
Abstract
The aim of this study was to investigate the genetic associations of ketosis and displaced abomasum with milk production traits in early first lactation of Canadian Holsteins. Health data recorded by producers were available from the national dairy cattle health system in Canada. Test-day records of milk, fat, and protein yields were obtained from the routine milk recoding scheme. Ketosis and displaced abomasum were defined as binary traits (0 = healthy; 1 = sick) based on whether or not the cow had at least 1 case of the respective disease in the period from calving to 100 d after calving. Mean frequencies of ketosis and displaced abomasum were 4.1 and 2.7%, respectively. The following milk production traits were considered: milk yield, fat percentage (Fat%), protein percentage (Prot%), fat-to-protein (F:P) ratio, and F:P ratio >1.5. The trait F:P ratio >1.5 was scored as 1 or 0, based on whether or not the cow had an F:P ratio >1.5. For milk production traits, the first (5-30 d in milk) and the second (31-60 d in milk) test days were considered. Data were analyzed using bivariate linear animal models. Average heritabilities of 0.02 and 0.04 were obtained for ketosis and displaced abomasum, respectively. For milk production traits, the lowest heritabilities were obtained for F:P >1.5 (0.04 to 0.08), whereas the highest estimates were found for Prot% (0.27 to 0.38). Ketosis and displaced abomasum were genetically uncorrelated with milk yield in early lactation. Moderate favorable correlations were found between metabolic diseases and milk composition traits. Ketosis was significantly correlated with Fat% (0.33), F:P ratio (0.30), and F:P ratio >1.5 (0.35) at the first test day, whereas all genetic correlations with milk composition traits at the second test day were not significant and close to zero. Significant favorable genetic correlations were also found between displaced abomasum and F:P ratio (0.26), F:P ratio >1.5 (0.25) and Prot% (-0.19) at the first test day. Also, Prot% at the second test day was significantly correlated (-0.16) with displaced abomasum. Overall, a higher Fat% and F:P ratio and a lower Prot% at the first test day were associated with an increased susceptibility to metabolic diseases. As genetic correlations between metabolic diseases and F:P ratio were far from unity, dairy producers should be encouraged to keep accurate and complete health data. This will be expected to yield to more accurate genetic evaluations for metabolic diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".