Identification of bioactive compounds with GC–Q-TOF–MS in the extracts from <i>Clinacanthus nutans</i> using subcritical carbon dioxide extraction
Bibliographic record
Abstract
Subcritical carbon dioxide Soxhlet extraction of biologically active compounds from Clincanthus nutans was investigated by full factorial design to identify and optimize the factors (particle size and co-solvent) affecting extract yield, antioxidant activity, total phenolic content, total flavonoid content, and α-glucosidase inhibitory activity. An average of 3.103% yield, 98.90% antioxidant activity, 49.40 mg/g (GAE) TPC, 43.76 mg/g (RE), and 88.58% AGI activity can be achieved using the optimum levels of independent variables. The GC-Q-TOF MS identification of optimized extract shown that different classes of phytoconstituents were successfully separated by CO2-Soxhlet to produce potential antioxidant and α-glucosidase inhibitory activity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".