Изучение полноценности белков в разных типах мыщц говядины
Bibliographic record
Abstract
The article presents the quantitative assessment of trends in the content of amino acids, which are manifested in long-term storage of beef. The content of protein-quality indicator in the meat of domestic and imported beef in various types of cuts in order to determine the biological value of meat was studied. This paper investigated the muscle of beef carcasses: gluteus medius, semitendinosus, semimembranosus, leading, scalloping, quadriceps, biceps femoris, triceps, supraspinatus, infraspinatus, longissimus dorsi, lower back, neck, and industrial beef cuts of domestic and foreign production. The study of the amino acid composition showed that the ratio of the content of essential amino acids to total amino acids was almost constant for all the muscles at the level of 39 41%, the ratio of isoleucine for methionine content in all cases was also a constant value of 0.6. The ratio of methionine to isoleucine free amino acids equal to 1 and greater than 35-40% of the same magnitude value related to amino acids in proteins, the amount of leucine in almost all examined muscles in 1,6-2,0 times the content of isoleucine. It is shown that the ratio of tryptophan to hydroxyproline was 0,8-4,8 muscle, which corresponds to the content of the connective tissue, 1.9% and 0.4 respectively. Analysis of the quality of imported cuts (Canada) and domestic beef has shown that the integral protein and a quality indicator can be used to estimate consumer qualities of meat. This index with a value of 0,531,01 in the samples of beef, except for the length of spinal muscles and cuts of beef, indicating fairly low biological value of meat cuts in the shoulder, hip, side, chest pieces, as well as the rear shank. Protein-quality indicator can be used to quantify the consumer properties of raw meat.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".