An eco-friendly method for analysis of sulfonamides in water samples using a multi-pumping system
Bibliographic record
Abstract
A new methodology for determination of sulfonamides (sulfaquinoxaline, sulfathiazole, and sulfadimethoxine) in water samples was developed by coupling an automated multi-pumping flow system (MPFS) with a liquid waveguide capillary cell (LWCC; pathlength, 100 cm) and a spectrophotometric detector. The method is based on the reaction between sulfonamides and p-dimethylaminocinnamaldehyde (p-DAC) in the presence of sodium dodecylsulfate (SDS) in dilute acid medium (hydrochloric acid), with measurement of the reaction products at 565 nm. Experimental design methodology was used to optimize the analytical conditions. The linear range obtained was 10.0–130.0 μg/L, and detection and quantification limits were 3.1 and 10.1 μg/L, respectively. The method was successfully applied to the analysis of sulfonamides in water samples. By coupling the MPFS with the LWCC, the sensitivity was enhanced, reagent consumption was low, and waste generation was minimized. The results obtained with the MPFS method were confirmed by LC–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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".