The development of a microwave-assisted extraction method for the determination of sulfonamide antibiotics in sediments and soils
Bibliographic record
Abstract
A microwave-assisted extraction technique was developed for the determination of nine sulfonamide antibiotics (sulfaguanidine, sulfacetamide, sulfadiazine, sulfathiazole, sulfapyridine, sulfamethazine, sulfamerazine, sulfamethoxazole, and sulfadimethoxine) in six sediments and soils of varying organic carbon content. Method optimization was performed using Lake Erie sediment and revealed the optimum extraction solvent to be methanol, with an extraction time of 45 min. After extraction, samples were “cleaned up” via filtration and quantified using LC-MS/MS spectroscopy. Method calibration curves were constructed in each environmental solid with sulfonamides ranging from 10 to 2000 ng/g; method detection limits were typically in the sub- to low nanograms per gram range. Method validation entailed spiking each solid at three different concentrations spanning the calibration curve (40, 300, and 800 ng/g); generally, method accuracy for spiked solids exceeded 80%, with precision being within 20%. Finally, we extracted sulfonamides from environmental solids (two sediments and one soil) that had been aged for 21 days and found that our method accuracy remained in excess of 80%. Moreover, absolute recoveries generally agreed with method accuracies (at the 95% confidence interval) in all environmental solids, demonstrating the efficiency of our microwave-assisted extraction procedure and its suitability for application to environmental samples.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".