Enantioseparation of Citalopram by RP-HPLC, Using Sulfobutyl Ether-<i>β</i>-Cyclodextrin as a Chiral Mobile Phase Additive
Bibliographic record
Abstract
Enantiomeric separation of citalopram (CIT) was developed using a reversed phase HPLC (RP-HPLC) with sulfobutylether-β-cyclodextrin (SBE-β-CD) as a chiral mobile phase additive. The effects of the pH value of aqueous buffer, concentration of chiral additive, composition of mobile phase, and column temperature on the enantioseparation of CIT were investigated on the Hedera ODS-2 C18 column (250 mm × 4.6 mm × 5.0 um). A satisfactory resolution was achieved at 25°C using a mobile phase consisting of a mixture of aqueous buffer (pH of 2.5, 5 mM sodium dihydrogen phosphate, and 12 mM SBE-β-CD), methanol, and acetonitrile with a volumetric ratio of 21 : 3 : 1 and flow rate of 1.0 mL/min. This analytical method was evaluated by examining the precision (lower than 3.0%), linearity (regression coefficients close to 1), limit of detection (0.070 µg/mL for (R)-CIT and 0.076 µg/mL for (S)-CIT), and limit of quantitation (0.235 µg/mL for (R)-CIT and 0.254 µg/mL for (S)-CIT).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".