New pressure‐assisted sweeping on‐line preconcentration for highly polar environmentally relevant nitrosamines: Part 2. Cationic and anionic surfactants with zero‐flow capillaries
Bibliographic record
Abstract
We recently introduced a pressure-assisted sweeping-reversed migration-EKC (RM-EKC) method for preconcentration of neutral polar N-nitrosamines with low affinity for the micellar phase. The type of surfactant and phase ratio are dominant factors in dictating the magnitude of interactions between analyte and micellar phase, thus four surfactants (anionic and cationic) with a range of functionalities (SDS, ammonium perfluorooctanoate (APFO), bile salts, and cetyltrimethylammonium chloride (CTAC)) were evaluated for sweeping-RM-EKC of highly polar N-nitrosamines. All gave acceptable results for sweeping-RM-EKC when used in high concentrations (≥200 mM) with low EOF. While no single surfactant was superior by all measures, all but the bile salts had useful performance characteristics. APFO showed the narrowest peak widths and highest number of theoretical plates, though two species co-migrated at all concentrations (25-300 mM); SDS and the cationic surfactant CTAC also showed good separation characteristics and could resolve all peaks, but CTAC had wider separation window. Various types of capillaries coated for EOF control were compared for use with anionic and cationic surfactants. A commercial zero-EOF capillary coated with a polymer bearing sulfonic acid functional groups showed superior EOF suppression and reproducibility of migration time with all surfactants.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".