POSITIONAL DISTRIBUTION OF FATTY ACIDS IN EGG YOLK LIPIDS
Bibliographic record
Abstract
ABSTRACT Numerous methods for the assessment of the positional distribution of fatty acids (FAs) in triacylglycerols (TGs) and phospholipids (PLs) have been described in the literature. Most of them employ enzymatic reactions or chiral separation by high‐performance liquid chromatography. Compared with most other food lipids, egg lipid has a rather unique composition, containing high amounts of TG as well as PL organized in lipoproteins. In this study, we demonstrate that the classical approach employing pancreatic lipase and phospholipase A2 is suitable for application to egg lipids. By using this method, the total distribution of FAs among the single positions of the main lipid classes in egg lipids can be measured in a rather straightforward way. Problems regarding accuracy, especially for the determination of minor and polyunsaturated fatty acids, are discussed. The presented method gave satisfactory results even for polyunsaturates such as docosahexaenoic acid down to amounts of 1% in a specific position.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 0.001 |
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".