A Microwave-assisted Extraction Method for the Determination of Synthetic Musks in Sewage Sludge
Bibliographic record
Abstract
Abstract An efficient microwave-assisted extraction (MAE) procedure has been optimized for the determination of polycyclic and nitro musks in sewage sludge. A centrifuged sludge cake sample (from 1 to 2.5 g ), mixed with 10 g of anhydrous sodium sulfate in a Teflon cell, was extracted with 30 mL of a 1:1 (v/v) mixture of acetone and hexane for 35 min, including a 15-min ramp with a 20-min hold at a controlled temperature of 110°C. After 30 min of cooling, the extract was evaporated and cleaned up on a silica gel column. A concentrated sample extract was then analyzed by gas chromatography/mass spectrometry (GC/MS) in the electron impact mode for the polycyclic musks and in negative ion chemical ionization mode for the nitro musks. This new method has been validated by comparing it to an established accelerated solvent extraction (ASE) method, with method detection limits ranging from 27 to 41 ng/g for the polycyclic musks, and approximately 4 ng/g for the nitro musks. Recoveries of most compounds in spiked samples ranged from 80 to 105%, although the MAE method produced lower recoveries for the nitro musks than the ASE method in archived sludge samples. The results generated by this MAE method were consistent with those prepared by previously reported techniques such as supercritical fluid extraction.
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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 | 0.001 | 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".