Tentative identification and quantification of TAG core aldehydes as dinitrophenylhydrazones in autoxidized sunflowerseed oil using reversed‐phase HPLC with electrospray lonization MS
Bibliographic record
Abstract
The molecular species of TAG core aldehydes (aldehydes still esterified to parent molecules) were detected and quantified in dietary-quality sunflowerseed oil autoxidized for 0-18 d at 60 degrees C in the dark. The analyses were performed by reversed-phase HPLC with UV (358 nm) absorption or light scattering and electrospray ionization-MS (ESI/MS) detection following preparation of the dinitrophenylhydrazone derivatives. Aldehyde production, as estimated by UV and ESI/MS, increased gradually over the 18-d period following a rapid initial destruction of the core aldehydes accumulated during storage of the commercial oil at 10 degrees C for 3 mon. The contents of hydroperoxides and hydroperoxide core aldehyde combinations were estimated to account for about 5% of total TAG, quantified as area in the chromatographic trace, after 18 d of autoxidation as estimated by an evaporative light scattering detector (ELSD). The major species of core aldehydes were tentatively identified as 9-oxononanoyl (70%)-, 12-oxo-9,10-epoxydodecenoyl (10%)-, and 13-oxo-9,11-tridecadienoyl (5%)-containing acylglycerols, plus smaller amounts of simple and mixed chain-length dialdehydes, and hydroxy and epoxy monoaldehyde-containing acylglycerols (15% of total). Quantitatively, the core aldehydes made up 2-12 g/kg of oil by UV detection and 2-9 g/kg of oil by ESI/MS detection, whereas the hydroperoxides measured in the unreduced state by HPLC with ELSD were estimated at 200 g/kg after 18 d of autoxidation. The major hydroperoxides of sunflowerseed oil were as previously identified.
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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) | 0.001 | 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) | 0.001 | 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".