Comparative analysis of the lipid profiles of bovine fast- and slow-type muscles
Bibliographic record
Abstract
Lipid molecules are an important component of meat and are the main source of flavor. However, at present the lipid molecules in meat with different muscle fiber types in cattle are not fully understood. We carried out lipid profiling of eight fast-type longissimus dorsi (LD) muscle and eight slow-type psoas major (PM) muscle samples from LYWC (Liaoyu white cattle). A total of 2032 lipid molecules were identified by our lipidomic analysis of these two muscle tissues, and 134 lipid species were identified as differentially abundant lipids (DALs). A correlation analysis showed the close relationship between the DALs identified in the LD and PM muscle. In addition, some DALs are closely associated with meat quality traits and muscle fiber types. This study identifies lipid molecules that differ between meats with different muscle fiber types and provides new insights into the role of lipids in beef quality improvement.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".