Meat productivity of young pigs of domestic, Canadian and French breeding
Bibliographic record
Abstract
Under the conditions of large pig-breeding complexes in the raw material zone of OJSC “Smolmyaso” (Smolensk region), LLC “Meat Processing Plant Stupinsky”, LLC APC “Mashkino” (Moscow region) during 2007–2017 a scientifi c and production experiment was carried out to determine the meat productivity of young pigs of domestic, Canadian and French breeding of diff erent breed combinations. When young pigs reached the live weight of 95–105 kg a control slaughter was carried out in order to determine the meat parameters of pig carcasses of the studied combinations. It has been revealed as a result of the experiment that three-breeds young pigs of French selection have the best meat qualities in terms of such indicators as the fat depth – 20,6 mm, which was less than the minimum indicators in the subgroups of three-breeds young pigs of domestic and Canadian breeding by 5,9 and 1,9 mm, and in terms of the area of the eye of loin – 55,7 mm, it surpassed these subgroups by 21,3 and 1,4 %, respectively. When determining the qualitative composition of pig carcasses, it has been concluded that three-breeds young pigs of Canadian and French breeding have approximately the same carcass meat content, but signifi cantly exceeded these indicators of three-breeds young pigs of domestic breeding in terms of pulp yield by 1,5 and 0,7 %, and the index of meatness of carcasses was higher by 0,9 and 0,6 %, respectively. It will be able to conclude on the basis of the results of scientifi c and production experiment that in order to obtain marketable young animals with high meat qualities, it is recommended to use more widely three-breeds hybrid young pigs of Canadian and French breeding
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".