Genes located on a SSC17 meat quality QTL region are associated with growth in outbred pig populations
Bibliographic record
Abstract
The objective of this study was to evaluate the effect of markers developed in eight genes, located in a previously detected meat quality QTL region on SSC17, on growth, fat and meat quality traits collected in commercial pig populations of different genetic backgrounds. The genes had been previously mapped to SSC17 as part of a fine-mapping effort. Association analyses were conducted between each marker and the available phenotypic traits. Results showed that three genes (CTSZ, CSTF1 and C20orf43) were significantly associated with the growth traits. In addition, CTSZ also impacted on meat colour, with the less favourable genotype for growth being associated with darker meat. The differences observed between genotypes were substantial and may be of economic importance to pig producers. These markers may be useful for selecting for faster growth or improved meat quality.
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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".