Automated Liquid–Liquid Extraction Method for High-Throughput Analysis of Rosuvastatin in Human EDTA K <sub>2</sub> Plasma by LC–MS/MS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Liquid-liquid extraction has been widely used for the analysis of rosuvastatin due to its many attractive features, such as low cost and clean extract. However, manual transfer of the organic phase poses a challenge, particularly when a batch size is large. To overcome the challenge, a simple automated high-throughput (192 samples per batch) liquid-liquid extraction method with short (3.0-min) chromatographic run time was proposed. Rosuvastatin was separated using a gradient on a reversed-phase C18 column and detected in the multiple reaction monitoring made with a mass transition of m/z 482.3→258.2 amu. RESULTS: The assay exhibited a linear range from 50 to 25000 pg/ml (r ≥ 0.9976). The intra- and inter-day accuracy ranged from 98.16 to 103.84% and 101.18 to 103.95%, respectively. The intra- and inter-day precision ranged from 0.70 to 6.17% and 2.19 to 5.07%, respectively. CONCLUSION: Finally, the validated method was successfully applied to bioequivalence studies.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 it