Dataset showing the relationship between terpenes, antioxidants and polyphenols in protecting ester and ether linked glycerophospholipids of grilled beef and moose meat marinated with unfiltered beer from oxidation
Bibliographic record
Abstract
[1], demonstrating the use of unfiltered beer-based marinades in improving the nutritional quality of grilled ruminant meat by suppressing the degradation of health-promoting ester and ether-linked PC and PE the most predominant glycerophospholipids (GPL) in meat. High throughput lipidomics analysis was conducted using high-resolution accurate mass tandem mass spectrometry (UHPLC-HRAMS/MS-MS) to profile the meat lipids following marination and grilling. The marinades were composed of a combination of unfiltered beers, fruits, herbs and spices. The data presented show the retention levels of ether as well as ester linked PC and PE molecular species; Pearson's correlations for the associations between antioxidants, phenolics, volatile oxygenated terpenes, oxidation status and preserved phospholipid species in the marinated grilled meats. There are many studies demonstrating cooking effects on fatty acid composition of meat phospholipids in the literature. However, information on how marination and grilling affects intact ether and ester linked PC and PE composition in grilled ruminant meats is limited. As such, this dataset provides useful information on the preservation of ruminant meat ester and ether-linked glycerophospholipid composition following marination with unfiltered beer-based marinades and meat preparation via grilling. Specifically, this data demonstrate the preservation of ether and ester linked PC and PE enriched with essential ω3 and ω6 fatty acids from degradation during grilling. For additional insights see [1] DOI: 10.1016/j.meatsci.2020.108271.
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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 | 0.001 | 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".