Ultrasonic extraction of ferulic acid from <i>Angelica sinensis</i>
Bibliographic record
Abstract
Abstract In this paper, the extraction of ferulic acid, a pharmacologically active ingredient from the root of Angelica sinensis with ultrasonic extraction was investigated. Percolation and supercritical fluid extraction (SFE) were also employed to make comparisons with ultrasonic extraction. Three variables, which including the concentration of solvent, the ratio of solvent volume to sample (mL/g), and extraction time, were found to have great influence on ultrasonic extraction. The optimum extraction conditions were using pure ethanol with a ratio of solvent volume to sample 8:1 (mL/g) and extraction time of 30 min. Under the optimum extraction conditions, the extraction yield could reach 6.5% mass fraction, which was higher than that of SFE process with ethanol as co‐solvent and nearly a content of ferulic acid 1.0%; both the yield and the content of ferulic acid were higher than those obtained by percolation. Moreover, the time of ultrasonic extraction was significantly shortened. Overall, Ultrasonic extraction was shown to be highly efficient in the extraction of ferulic acid from Angelica sinensis .
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".