Simultaneous and recursive random regression models for milk yield and somatic cell score in Canadian Holsteins
Bibliographic record
Abstract
Random regression models with simultaneous and recursive links between phenotypes for milk yield and somatic cell score (SCS) on the same test-day were fitted to Canadian Holstein data. Heterogeneity of structural coefficients was allowed for across (the first 3 lactations) and within (4 days in milk intervals) lactation. Model comparisons indicated superiority of simultaneous models over recursive and standard multiple-trait models. A moderate heterogeneous (both across and within lactation) negative effect of SCS on milk yield and a smaller positive reciprocal effect of SCS on milk yield were estimated in the most plausible specification. Estimates of genetic parameters on a daily basis differed while rankings of bulls and cows for 305d milk yield, average daily SCS and milk lactation persistency remained the same among models. No apparent benefits are expected due to fitting causal phenotypic relationships between milk yield and SCS in the random regression TD model for genetic evaluation purposes.
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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 | 0.001 | 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) | 0.001 | 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 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".