Comparative analysis of flavoromic and metabolomic profiling differences between red, firm and non-exudative (RFN) and pale, soft and exudative (PSE) pork
Bibliographic record
Abstract
This research aimed to identify different flavors and metabolites between red, firm and non-exudative (RFN) and pale, soft and exudative (PSE) pork. In this study, the meat quality of RFN and PSE meat was examined, which showed that drip loss, shear force and meat color ( L* value) of PSE meat were markedly higher than those for RFN meat. A total of 1545 flavor compounds were identified in RFN meat and PSE meat, of which 126 had differential abundance between the two types of meat. Furthermore, 19 aroma compounds had ROAV values greater than 1. Metabolomic analysis identified 32 metabolites that had different abundances between RFN and PSE meat. KEGG enrichment analysis of these differential metabolites yielded marked enrichments in 30 signaling pathways including purine metabolism and FoxO signaling pathway. The results of this research identify new perspective into biomarkers flavor compounds and metabolites that differ between RFN and PSE pork.
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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) | 0.001 | 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".