Genetic parameters for somatic cell score in the first three lactations of Czech Holstein and Fleckvieh breeds using a random regression model
Bibliographic record
Abstract
A multiple-lactation random regression model was applied to test-day somatic cell score (SCS) records from the first three lactations of Czech Holstein and Fleckvieh cows. For Holstein, the data included 26 314 cows, with 244 953, 76 188 and 26 153 test-day records in the first, second and third lactation, respectively. For Fleckvieh, the data included 24 061 cows, with 223 421, 93 358 and 31 305 test-day records in the first, second and third lactation, respectively. The linear model for SCS included the following factors (for the given parity): fixed herd-test date effect, fixed regressions on days in milk within the age-season class, random regressions for the animal genetic and random regressions for the permanent environmental effect of the cow. Third-degree Legendre polynomials were used for all regressions. Gibbs sampling was used to generate samples from the marginal posterior distributions of the model parameters. The resulting daily heritability ranged from 0.08 to 0.11 in the middle part of lactation and it increased only slightly with parity. Extremely high values (0.25, 0.21) observed especially at the beginning and end of the third lactation for Holstein might be caused by the "end-of-range" problem. The average daily heritabilities computed for the part of lactation between 45 and 255 days in milk (DIM) were in the range from 0.10 to 0.14. Daily permanent environmental variances were higher than the genetic variances and daily residual variances decreased with DIM. The residual variances in early lactation increased with lactation number. For both breeds, the highest genetic correlations computed for the part of lactation between DIM 45 and DIM 255 were obtained between the second and third lactation (0.95). The lowest daily genetic correlations of SCS in the same DIM between different lactations occurred at the beginning of lactation, especially between the first and third lactation. The permanent environmental correlations for selected DIM were lower than the respective genetic correlations.
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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 | 0.001 | 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".