Acesulfame-K and pharmaceuticals as co-tracers of municipal wastewater in a receiving river
Bibliographic record
Abstract
Wastewater treatment plant (WWTP) effluents are important sources of emerging contaminants at environmentally-relevant concentrations. In this study, water samples were collected from a river downstream of two WWTPs to identify practical tracers for tracking wastewater. The results of the study indicate elevated concentrations of Cl(-), nutrients (NH3-N and NO2(-)), the artificial sweetener acesulfame-K (ACE-K), and the pharmaceuticals carbamazepine (CBZ), caffeine (CAF), sulfamethoxazole (SMX), ibuprofen (IBU), gemfibrozil (GEM), and naproxen (NAP) in the river close to the WWTPs that decreased with distance downstream. A correlation analysis using the Spearman Rank method showed that ACE-K, CBZ, GEM, NAP, and Cl(-) were strongly correlated with each other over a 31 km stretch of the river in the study area. The strong correlations of these target compounds indicate that the artificial sweetener ACE-K and the pharmaceuticals CBZ, GEM, and NAP can potentially be used as co-tracers to track wastewater.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".