Caracterización de algunos genes candidatos de la adiposidad en cerdos pío negro del País Vasco y "large white"
Bibliographic record
Abstract
Fatness is a highly heritable quantitative trait strongly influenced by the environment, so only mutations with very large effects are likely to be detected (Keightley, 1995). Breeds with a high adipose development offer an opportunity for this detection. An example is the Basque Black Pied, one of those pig breeds that have lost its productive role during the last century (Iriarte and Alfonso, 2000). The Basque breed exhibited an early and higher adipose development and a higher activity of enzymes responsible for lipid synthesis than selected pig populations (Alfonso et al., 2005). Laval et al. (2000), in a study of pig genetic diversity, indicated that the Basque breed appeared to be the most unique in the set of eleven pig breeds originating from six European countries they analysed. So, the Basque Black Pied can be considered as an interesting pig population to analyse candidate genes of fat tissue development. Several candidate genes, mapped functional genes related to the expression of a trait, have been suggested to explain pig fatness. Four of them are characterised in this work: the Heart Fatty Acid-Binding Protein (H-FABP), the Adipocyte Fatty Acid-Binding Protein (A-FABP), the Porcine Leptin Receptor (LEPR) and the Porcine Leptin (LEP). Associations between them and intramuscular fat content and backfat thickness have been found in different studies (Estany et al., 2002; Gerbens et al., 1998; Gerbens et al., 1999; Kennes et al., 2001).
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".