The relationship between the polymorphism of the porcine <i>CAST</i> gene and productive traits in pigs
Bibliographic record
Abstract
Urbański, P., Pierzchała, M., Terman, A., Kamyczek, M., Różycki, M., Roszczyk, A. and Czarnik, U. 2015. The relationship between the polymorphism of the porcine CAST gene and productive traits in pigs. Can. J. Anim. Sci. 95: 361–367. The aim of the study was to characterize the polymorphism of the calpastatin gene identified with ApaLI, Hpy188I and PvuII restriction enzymes in two pig breeds and one line bred in Poland, and to evaluate the relationship between the CAST genotype and carcass traits. The analysis covered a total of 617 pigs of two breeds, Polish Landrace (185) and Polish Large White (216), and synthetic line L990 (216). All animals studied appeared to be monomorphic at two loci: CAST/ApaLI and CAST/Hpy188I, while three genotypes were observed at CAST/PvuII locus. Statistical analysis was carried out for each breed separately using the least square methods of the GLM procedure. The model included the effect of the CAST genotype, fixed effect of the RYR1 genotype and the effect of the sire. Because the RYR1 genotype could significantly modify the effect of other genes, the effect of the RYR1 genotype was included in the statistical model. The relationship between the polymorphism and several productive traits was identified in each of the study groups of pigs. Animals carrying the heterozygous genotype at this locus showed most extreme values for some of the traits tested. Our results suggest that the CAST /PvuII genotype might be utilized in the selection of valuable pig carcass traits, particularly weight and size of the loin.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 source (direct Gemma or distilled Codex), 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".