Partitioning of Multiple-Trait Model Parameters with Respect to Phenotypic Recursion: Case Study of Birth Weight and Calving Ease in Canadian Simmentals
Bibliographic record
Abstract
Fully recursive model (RM) is equivalent to a multiple-trait model (MTM). Structural coefficients and other RM parameters can be derived from MTM parameters given a known causal structure. Birth weight (BW) and calving ease (CE) of Canadian Simmental cattle were analyzed by a linear-binary MTM with direct and maternal genetic effects. Direct and indirect (mediated by BW) genetic and environmental effects on CE were quantified by transformation of MTM parameters. An increase of 1 kg of BW resulted in more difficult calving by 0.044 on a liability scale. Variance due to direct effects on CE constituted from 71 to 100% of the total variance for different sources of variability. Random MTM effects were correlated almost perfectly with direct RM effects. Correlations between direct and indirect RM effects on CE were smaller than 0.66.
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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".