Contamination patterns and attenuation of pharmaceuticals in a temporary Mediterranean river
Bibliographic record
Abstract
The contamination patterns and fate of pharmaceutically active compounds (PhACs) were investigated in the Evrotas River (Southern Greece). This is a temporary river with differing levels of water stress and water quality impairment in a number of its reaches. Three sampling campaigns were conducted in order to capture different levels of water stress and water quality. Four sampling sites located on the main channel of the Evrotas River were sampled in July 2015 (moderate stream flow), and June and September 2016 (low stream flow). Discharge of urban wastewater has been determined as the main source of pollution, with PhACs, nutrients and other physicochemical parameters considerably increasing downstream the wastewater treatment plant (WWTP) of Sparta city. Due to the pronounced hydrological variation of the Evrotas River, generally, the highest concentrations of PhACs have been detected during low flow conditions. Simultaneously, low flow resulted in an increased water travel time and consequently longer residence time that accounted for the higher attenuation of most PhACs. The average decrease in total concentration of PhACs within the studied waterbody segment (downstream of Sparta city) increased from 22% in July 2015 to 25% in June 2016 and 77% in September 2016. The PhACs with the highest average concentration decrease throughout the sampling campaigns were hydrochlorothiazide, followed by sotalol, carbamazepine, valsartan, and naproxen.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".