The Isolation of Yellow Mustard Oil Using Water and Cyclic Ethers
Bibliographic record
Abstract
Abstract An aqueous extraction process (AEP) was developed for dehulled yellow mustard flour with the aim of producing yellow mustard oil for industrial applications, as a by‐product of food protein production. During AEP, most of the oil extracted was bound in a stable oil‐in‐water emulsion that must be destabilized to recover free oil. The oil distribution after aqueous extraction and the composition of the emulsion produced were determined. The emulsion was solubilized in organic solvents including tetrahydrofuran (THF) and 1,4‐dioxane to fully recover the oil in a single‐phase oil–solvent‐water miscella. Over 97 and 95% of the oil in the emulsion was successfully recovered using 4:1 THF:oil and 9:1 dioxane:oil weight ratios, respectively. The oil recovery from the emulsion was optimized, based on experimentally prepared ternary phase diagrams of THF/oil/water and dioxane/oil/water. The results suggest that this technically viable approach can successfully recover essentially all of the oil from the emulsion, equivalent to an overall free oil recovery of ~63% from dehulled yellow mustard flour.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".