pH-Independent large-volume sample stacking of positive or negative analytes in capillary electrophoresis
Bibliographic record
Abstract
In capillary electrophoresis, the short optical path length associated with on-column UV detection imposes an inherent detection problem. Detection limits can be improved using sample stacking. Recently, large-volume sample stacking (LVSS) without polarity switching was demonstrated to improve detection limits of charged analytes by more than 100-fold. However, this technique requires suppression of the electroosmotic flow (EOF) during the run. This necessitates working at a low pH, which limits using pH to optimize selectivity. We demonstrate that LVSS can be performed at any buffer pH (4.0-10.0) if the zwitterionic surfactant Rewoteric AM CAS U is used to suppress the EOF. Sensitivity enhancements of up to 85-fold are achieved with migration time, corrected area, and peak height reproducibility of 0.8-1.6%, 1.3-3.7%, and 0.8-4.9%, respectively. Further, it is possible to stack either positively or negatively charged analytes using zwitterionic surfactants to suppress the EOF.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".