Rapid Method for Determination of Residual tert-Butanol in Liposomes Using Solid-Phase Microextraction and Gas Chromatography
Bibliographic record
Abstract
A simple, rapid, and reliable method to detect residual levels of tert-butanol in liposomes using sec-butanol as an internal standard has been developed. Solid-phase microextraction (SPME) followed by gas chromatographic analysis was used to quantify the amount of residual tert-butanol in freeze-dried liposome material. Only 1 min was necessary for reproducible amounts of analyte to absorb onto the SPME fiber, and because this method requires very little sample preparation, a single analysis can be completed in less than 15 min. This method had a linear range of 10-600 microg/mL. Careful control of times of temperature equilibration and exposure to headspace was necessary to ensure reproducible results. This method can easily be applied to other applications in the food and pharmaceutical industries where detection of residual solvents, such as hexane and chloroform, is necessary.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".