Aqueous enzymatic extraction and quality evaluation of <i>Acer truncatum</i> Bunge seed oil
Bibliographic record
Abstract
Abstract Aqueous enzymatic extraction (AEE) of oil from Acer truncatum Bunge seed kernel was investigated. The effects of enzyme type on the extraction yield of oil were studied, and the results showed that the oil yield obtained with pentosanase was higher than that obtained with the other enzymes. The combination of pentosanase and cellulase showed better extraction performance than a single enzyme, and the operation parameters of the AEE method were optimized. A maximum oil yield of 37.94% was obtained. The analysis results of chemical compositions of the extracted oils showed that the content of unsaturated fatty acids in the oil extracted by the AEE method was 90.28%, and the content of nervonic acid was about 5.59%. In addition, the main physical and chemical properties of A. truncatum Bunge seed oil were measured. The oil obtained by the AEE method met the China National Standard of A. truncatum Bunge oil.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.000 | 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".