Identification of glycerophospholipids in rapeseed, olive, almond, and sunflower oils by LCMS and LCMSMS
Bibliographic record
Abstract
HPLC employing a thermostatted Lichrospher 100 diol column was used to separate mixtures of glycerophospholipids of rapeseed, olive, almond, and sunflower oils. Elution was performed with a binary gradient of two mixed solvents A: hexane isopropanol acetic acid triethylamine (82:17:1.0:0.08 v/v/v/v) and B: isopropanol water acetic acid triethylamine (85:14:1.0:0.08 v/v/v/v). The LC effluent was directly introduced into the mass spectrometer through an electrospray capillary. Information about the fatty acid composition of each glycerophos pho lipid class was given by tandem mass spectrometry (MSMS). These techniques permitted a rapid separation and identification of complex mixtures of glycerophospholipids. The relative abundance of each lipid class in each oil was also determined. The resulting glycerophospholipid signature may provide an efficient means of identifying oil origin and possible adulteration.Key words: glycerophospholipids, vegetable oils, tandem mass spectrometry, LCMS.
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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) | 0.001 | 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 | 0.000 |
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".