Determination of phenyl-<i>N</i>-methylcarbamates and their hydrolysis products in water, using solid-phase extraction and reversed-phase liquid chromatography with UV and electrospray mass spectrometric detection
Bibliographic record
Abstract
In this study, eight phenyl-N-methylcarbamates (PNMCs) were considered. Reversed-phase LC was set up for UV and mass spectrometry (MS) detection mode. Gradient elution was used, and the mobile phase was composed of acetonitrile and water. UVvis was performed at 220 nm. The method was tested with different reversed-phase columns. Comparison between chromatographic parameters: retention time (tR), resolution (RS), and selectivity (α) was established. Hydrolysis kinetics of three of the PNMCs were reported. The major hydrolysis products were determined by LCUV, and the effect of pH on hydrolysis was also studied. Also, chromatographic separation of a mixture of PNMCs and four of their hydrolysis products was carried out. The preconcentration of 12 studied solutes was realized by solid-phase extraction. C18 extraction cartridges of 1 g were used to extract solutes from a 100 mL volume of tap and surface water spiked at 10 µg/L. The recoveries were, respectively, between 6886% and 6283% with relative a standard deviation of less than 11%. Limits of detection (LODs) and limits of quantitation (LOQs) ranged, respectively, from 14 µg/L and from 410 µg/L. Since standard UV detection does not provide adequate selectivity for water samples, an electrospray (ES)-MS instrument equipped with a triple quadrupole mass filter was used. MS data acquisition was performed by a time-scheduled, selected-ion monitoring (SIM) program. Limits of quantitation gave values between 0.10.5 µg/L.Key words: phenyl-N-methylcarbamates, water analysis, solid-phase extraction, LCUVvis, LCES-MS.
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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 | 0.000 | 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 | 0.001 | 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".