Genomic Prediction for Reproductive Traits of Commercial Sows in Health Challenged Herds
Bibliographic record
Abstract
The present study performed genomic prediction for reproductive performance of sows in commercial farms with a history of health problems. Accuracies of genomic predictions for lifetime performance were low to moderate, ranging from 0.11 (TNB) to 0.45 (NBD). Accuracies of genomic prediction for later parity performance using parity 1 performance were low, ranging from -0.07 (NSB in parity 3) to 0.19 (NBD in parity 2), with average accuracies by trait ranging from 0.04 (NSB) to 0.16 (NBD). Although most accuracies were low, the moderately high accuracies for some lifetime performance traits shows that genomic prediction can be used to improve reproductive performance in commercial sows.
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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".