Pharmaceutically active compounds in water, Aksaray, Turkey
Bibliographic record
Abstract
Pharmaceutically active compounds (PACs) are widely used around the world to maintain human and animal health. There is growing concern that these compounds pass through sewage‐treatment plants and enter the environment for potential harmful effects on living things. In this study, the occurrence of nine PACs (acetaminophen, caffeine, carbamazepine, codeine, methyltestosterone, metoprolol, propranolol, stanozolol, and testosterone) in hospital wastewater, sewage wastewater, raw water used for drinking water, and treated water was studied in three sampling events representing different flow conditions, i.e., December, April, and June 2010–2011. Most of the target compounds were detected in both hospital and sewage wastewater samples rather than in drinking water samples. The most frequently detected compounds in the samples were acetaminophen and caffeine with increased concentrations of up to 160 µg/L in sewage wastewater, while their concentrations were significantly lower in raw water. Generally, a seasonal variation of the test compounds in the samples was significant. All drugs were detected in higher levels during winter as drug use for diseases might increase through this season and a faster degradation and removal might occur during summer. The results showed that water had been polluted with these substances, and although purified by water treatment, reached humans via drinking water.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.012 |
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; both teacher heads agree on what is shown here.
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".