ИСПОЛЬЗОВАНИЕ ХРЯКОВ КАНАДСКОЙ СЕЛЕКЦИИ ДЛЯ УЛУЧШЕНИЯ МЯСНЫХ КАЧЕСТВ СВИНЕЙ КРУПНОЙ БЕЛОЙ ПОРОДЫ
Bibliographic record
Abstract
Three experiments were carried out to improve the meat productivity of pigs of Large White (LW) breed of russian selection by different variants of crossing with the Yorkshire (Y) breed of canadian selection. There were no significant differences between the groups in terms of reproductive qualities. Two-breed pigs (LW x Y) grew more intensively and the live weight of the piglet at the 30 days was 8,7 kg, which is higher than in the other groups with a significant difference (P <0,05). When the live weight of 100 kg was reached, the вackfat thickness of the fat over 6-7 thoracic vertebrae was 26,3 mm compared to 30,7 mm in purebred pigs of the LW of the breed (P <0,001), the area of the muscular eye was respectively 45,1 cm 2 and 30,6 cm 2 (P <0,001). In the fourth generation of reproductive and absorbent crossing of pigs of LW and Y of breeds, the thickness of the fat on the carcasses of pigs was 21,2 mm (Р < 0.001), which is 30-39 % less than for the LW carcasses, the area of the muscular eye was 44 mm. In three-breed hybrids (LW x D) x L, the age of reaching 100kg was less by 12,5 days (P <0,01), the thickness of the fat was 23,6 mm, that is, it was 11,4 mm less (P < 0,001) in comparison with the control group. The replacement pigs obtained from the absorbent crossing (LW x Y) x Y showed the best results for the вackfat thickness - 19,2 mm, but they were inferior to the purebred Y (13,0 mm) (P <0,001). In the sows of this combination, 11,6 piglets were born alive, the number of piglets at weaning was 10,6, the weight of the nest in the 30-day was 78,7 kg. Differences in the frequency of occurrence of certain antigenic factors of blood in animals of different combinations of breeds are revealed. In animals that have the EAE allele edf, a higher growth rate is revealed, but thicker the backfat.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".