Effect of refrigeration on the collagen and texture characteristics of yak meat
Bibliographic record
Abstract
To investigate the effect of refrigeration on the collagen and texture characteristics of yak meat, the changes in collagen content, solubility, shear force, hardness, cohesiveness, springiness, gumminess, and chewiness of yak meat at 4 ± 1 °C were measured. The results showed that the contents and solubility of collagen in yak meat significantly decreased (P < 0.05). The myofibrillar fragmentation index of yak meat significantly increased (P < 0.05). The shear force, hardness, cohesiveness, springiness, gumminess, and chewiness of yak meat significantly decreased (P < 0.05). Correlation analysis and histological structure analysis confirmed that myofibrillar fragmentation and collagen characteristics significantly affected the formation of yak meat texture during refrigeration. After 5 d of refrigerated storage, yak meat has a higher quality. The results provide a theoretical basis and data to support the deep processing and quality control of yak meat.
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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 | 0.001 |
| 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) | 0.002 | 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".