Ammonium perfluorooctanoate as a volatile surfactant for the analysis of <b><i>N</i></b>‐methylcarbamates by MEKC‐ESI‐MS
Bibliographic record
Abstract
Ammonium perfluorooctanoate (APFOA) was investigated as an MS-friendly surfactant for the analysis of a mixture of ten N-methylcarbamates with MEKC-ESI-MS. Because of the relatively low boiling point of perfluorooctanoic acid ( approximately 190 degrees C), APFOA can be introduced into a mass spectrometer without the adverse effects of less volatile surfactants such as SDS. With a BGE consisting of 50 mM APFOA/isopropanol (IPA) 98:2 and with 30 kV applied, a very fast separation ( approximately 6 min) was possible with only one pair of analytes comigrating. Using an experimental design with four factors (voltage, nebulizer pressure, concentration of APFOA, and concentration of IPA) we were able to resolve all analytes in just over 11 min. Sheath liquid composition and flow rate, drying gas temperature and flow rate, and fragmentor voltage were then optimized for maximum signal intensity and S/N. It was found that the faster method gave better S/N because of narrower peak widths, and detection limits in SIM mode were between 0.01 (aldicarb) and 0.08 mg/L (methomyl). Calibration curves were prepared with standards of 0.50, 1.00, and 2.00 mg/L for the analysis of samples obtained after SPE of tap water spiked with the ten N-methylcarbamates at a level of 10 microg/L. All analytes showed very good recoveries (>86%), except for the most polar analyte aldicarb sulfone (recovery of 73%), testifying for the potential use of APFOA for this kind of analyses.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".