Optimization of ultrasonic‐assisted extraction of 3‐monochloropropane‐1,2‐diol (MCPD) and analysis of its esters from edible oils by gas chromatography–mass spectrometry
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Bibliographic record
Abstract
In this paper, ultrasonic-assisted extraction of 3-chloropropane-1,2-diol and its esters from edible oils was studied with isotope dilution GC-MS. Effects of several experimental parameters, such as types and concentrations of extracting solvent, ratios of liquid to material, extraction temperature, time of ultrasonic treatment on the extraction efficiency of 3-chloropropane-1,2-diol and its esters from edible oils and sample preparation for calibration were compared and optimized. The optimal extraction conditions were suggested as 66 mg oil sample in mixture of 0.5 mL MTBE/ethyl acetate (20% v/v) and 0.5 mL of sulfuric acid/n-propanol (0.3% v/v), being extracted for 30 min at 45°C under ultrasonic irradiation. Good linearity was gained in the range of 0.020-5.000 μg/g with the limit of detection (LOD) of 0.006 μg/g (S/N = 3) and the limit of quantification (LOQ) of 0.020 μg/g (S/N = 10). The recoveries at five spiked concentrations were ranged from 91.9 to 109.3% with RSD less than 9.4%. The method was successfully applied to the determination of 3-chloropropane-1,2-diol and its esters amounts in rapeseed, sesame, peanut, camellia, and soybean oils.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it