Study of the effect of the operating parameters on the separation of bioactive compounds of palm oil by ultra‐high performance supercritical fluid chromatography using a design of experiments approach
Bibliographic record
Abstract
Abstract In this study, an analytical method based on Design of Experiments and response surface methodology for the separation of lycopene, beta‐carotene, coenzyme Q10, and lutein was developed by ultra‐high performance supercritical fluid chromatography technique. A Central Composite Design was used to evaluate the influence of temperature, pressure, and ethanol percentage on the retention and separation factors of these compounds. In the designed experiments, the temperature was varied between 25 and 50 °C (298 and 323 K), the pressure within the interval of 1500 and 2200 psi (10 and 15 MPa), and the ethanol percentage between 15 and 24 (v/v) %. Each variable was tested at 3 levels and 5 replicated central points were added. It was found for the studied system that the ethanol percentage and pressure were the parameters that most influenced the retention factors whereas the ethanol percentage, pressure, and temperature affected the separation factors. Quadratic models were necessary to describe the retention and separation of these compounds. Furthermore, interactions among the factors were observed, justifying the DOE approach used in this work. Considering the retention and separation factors, the selected operating conditions for further experiments were: 15.5 % of ethanol at 40 °C (313 K) and 1500 psi (10 MPa).
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".