Lipase-catalyzed glycerolysis extended to the conversion of a variety of edible oils into structural fats
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Lipase-catalyzed glycerolysis was recently shown to be a viable technique to structure cottonseed and peanut oils into structural fats by converting native triacylglycerols into partial glycerides without changing overall fatty acid composition. Here, this approach was extended to a variety oils of differing fatty acid compositions. Reactions were performed at 65 °C for 48 h at a triacylglycerol:glycerol molar ratio of 1:1, using the non-regiospecific Candida antarctica lipase B. In all oil systems, a 20 °C increase in crystallization onset temperature was observed following glycerolysis. Solid fat content increases resulting from glycerolysis were greatest for oils containing >10% saturated fat along with a high oleic acid content. The solid fat content of tigernut oil at 5 °C increased from 8% to 34% following glycerolysis. Tigernut glycerolysis product was used to make margarine with plasticity similar to commercial margarine and butter. This research demonstrates that glycerolysis is a general strategy to convert liquid oils into structural fats used in food applications, and thus replace palm oil and hydrogenated fats.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 it