Different Tocopherols and the Relationship between Two Methods for Determination of Primary Oxidation Products in Fish Oil
Bibliographic record
Abstract
The effectiveness of 2.32 mmol/kg (approximately 1000 ppm) of alpha-, gamma-, or delta-tocopherol (TOH), as well as different levels of alpha TOH, on the formation of hydroperoxides in fish oil was studied by monitoring the peroxide value (POV) and the formation of conjugated dienes (CD) during storage at 30 degrees C. The same order of antioxidant activity was observed by both methods. Linear regression of POV on CD showed that these data were strongly correlated (r(2) > or = 0.98). The value of the slope of the regression lines, however, differed substantially and decreased with increasing hydrogen-donating ability of the different tocopherols and with increasing alpha TOH concentration. It is suggested that this is due, at least in part, to the contribution from hydroxy compounds to the CD measurements and a greater contribution from hydroperoxy epidioxides (two peroxide groups per conjugated diene unit) to the POV than to the CD value. The degrees of formation of both these groups of oxidation products are expected to be influenced by the rate of scavenging of lipid peroxyl and alkoxyl radicals by tocopherol (alpha TOH > gamma TOH > delta TOH).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".