Lipase‐catalyzed transesterification of trilinolein or trilinolenin with selected phenolic acids
Bibliographic record
Abstract
Abstract The enzymatic transesterification of selected phenolic acids with TAG, including trilinolein (TLA) and trillinolenin (TLNA), was investigated in an organic solvent medium. Maximal bioconversion of 66% was obtained with a dihydrocaffeic acid (DHCA) to TLA ratio of 1∶2 after 5 d of reaction. Similarly, the highest bioconversion of 62% was obtained with a DHCA to TLNA ratio of 1∶2, but after 12 d of reaction. However, a ratio of 1∶4 DHCA/TLA decreased the bioconversion to 53%. Transesterification reactions of ferulic acid with both TAG, using a ratio of 1∶2, resulted in low bioconversion of 16 and 14% with TLA and TLNA, respectively. The overall results indicated that bioconversion of phenolic MAG was higher than that of phenolic DAG. The structures of mono‐ and dilinoleyl dihydrocaffeate as well as those of mono‐ and dilinolenyl dihydrocaffeate were confirmed by LC‐MS analyses. The phenolic lipids demonstrated moderate radical‐scavenging activity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".