Separation of the Fatty Acids in Menhaden Oil as Methyl Esters with a Highly Polar Ionic Liquid Gas Chromatographic Column and Identification by Time of Flight Mass spectrometry
Bibliographic record
Abstract
The fatty acids contained in marine oils or products are traditionally analyzed by gas chromatography using capillary columns coated with polyethylene glycol phases. Recent reports indicate that 100 % cyanopropyl siloxane phases should also be used when the analyzed samples contain trans fatty acids. We investigated the separation of the fatty acid methyl esters prepared from menhaden oil using the more polar SLB-IL111 (200 m × 0.25 mm) ionic liquid capillary column and the chromatographic conditions previously optimized for the separation of the complex mixture of fatty acid methyl esters prepared from milk fat. Identifications of fatty acids were achieved by applying Ag(+)-HPLC fractionation and GC-TOF/MS analysis in CI(+) mode with isobutane as the ionization reagent. Calculation of equivalent chain lengths confirmed the assignment of double bond positions. This methodology allowed the identification of 125 fatty acids in menhaden oil, including isoprenoid and furanoid fatty acids, and the novel 7-methyl-6-hexadecenoic and 7-methyl-6-octadecenoic fatty acids. The chromatographic conditions applied in this study showed the potential of separating in a single 90-min analysis, among others, the short chain and trans fatty acids contained in dairy products, and the polyunsaturated fatty acids contained in marine products.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".