Comparison of Canola Meals Obtained with Conventional Methods and Supercritical CO<sub>2</sub> with and without Ethanol
Bibliographic record
Abstract
Abstract Canola meal is a potentially valuable protein source. Canola meals extracted with supercritical CO 2 (SC‐CO 2 ) were compared to pressed meal and meals extracted with hexane. With regard to the chemical composition, the glucosinolate, phenolic acid, tannin and phosphorus contents were determined in addition to proximate analysis. As for functionality, color, nitrogen solubility index (NSI), water and fat absorption, emulsifying capacity and stability, and overrun were determined. Both hexane‐ and SC‐CO 2 ‐extracted meals had a higher protein content than the pressed meal. The SC‐CO 2 ‐extracted meal had lower glucosinolate and higher phosphorus contents than hexane‐extracted meal. The phenolic acid contents of hexane‐ and SC‐CO 2 ‐extracted meals were similar, but were higher than those of meals extracted with SC‐CO 2 + ethanol. The color values of SC‐CO 2 ‐ and hexane‐extracted meals were similar and both were brighter than commercial meals (pressed and toasted). The NSI levels of SC‐CO 2 ‐ and hexane‐extracted meals were similar, but three times that of the commercial meal. Both hexane‐ and SC‐CO 2 ‐extracted meals had high water holding capacity, oil absorption, emulsifying capacity, emulsion stability and overrun. Canola meal extracted with SC‐CO 2 was similar to hexane‐extracted meal in terms of both chemical composition and functionality, but was superior to commercial meals.
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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 | 0.001 |
| 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 | 0.000 | 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".