Optimization of Microwave-Assisted Extraction (MAP) for Ginseng Components by Response Surface Methodology
Bibliographic record
Abstract
Response surface methodology (RSM) was applied to predict optimum conditions for microwave-assisted extraction-a MAP technology-of saponin components from ginseng roots. A central composite design was used to monitor the effect of ethanol concentration (30-90%, X(1)) and extraction time (30-270 s, X(2)) on dependent variables, such as total extract yield (Y(1)), crude saponin content (Y(2)), and saponin ratio (Y(3)), under atmospheric pressure conditions when focused microwaves were applied at an emission frequency of 2450 MHz. In MAP under pre-established conditions, correlation coefficients (R (2)) of the models for total extract yield and crude saponin were 0.9841 (p < 0.001) and 0.9704 (p < 0.01). Optimum extraction conditions were predicted for each variable as 52.6% ethanol and 224.7 s in extract yield and as 77.3% ethanol and 295.1 s in crude saponins, respectively. Estimated maximum values at predicted optimum conditions were in good agreement with experimental values.
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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) | 0.001 | 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 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".