Estimation of genetic and non‐genetic effects on productive life of Iranian Holstein dairy cows
Bibliographic record
Abstract
Understanding the factors that influence the lifespan of dairy cows is crucial for enhancing their productive life (PL). This study aimed to investigate the impact of genetic and environmental effects on the PL of Holstein cows. Data included 82,505 cows from 1952 sires that calved for the first time between 2001 and 2016. PL was defined from first calving to culling. Proportional hazard models, assuming a piecewise Weibull distribution of the baseline hazard function, were utilized to account for time-dependent effects, such as herd size variations, year-season, milk yield, fat and protein contents, and the time-independent fixed effect of age at first calving. Herd-year and sire effects were considered as random effects. All effects showed significant associations with PL (p < 0.001). The relative risk of culling was higher in heifers that calved at an older age and cows that calved during the cold season. Moreover, cows with lower production had a significantly shorter PL compared with high-producing cows. The effective heritability in the absence of censored data was estimated at 0.15. These findings suggest that greater attention should be paid to regular and accurate breeding programs, which are essential for enhancing profitability and the PL of Iranian dairy cows.
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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 | 0.000 |
| 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) | 0.000 | 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".