Pharmaceuticals in the Yamaska River, Quebec, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Pharmaceutically active compounds have been detected in North America and Europe in groundwater, surface water, wastewater, and drinking water. In the province of Quebec in Canada, there has been little data to assess the occurrence of pharmaceutical residues in the aquatic environment. In August of 2005, samples of surface water were collected at 10 sites along the Yamaska River basin in Quebec, which passes through important agricultural areas and receives wastewater from several urban centers with populations ranging up to 44,000 residents. Several acidic drugs (naproxen, ibuprofen, gemfibrozil), neutral drugs (caffeine, carbamazepine, cotinine), and the sulfonamide antibiotic sulfamethoxazole were detected in the majority of the surface water samples. The antidepressant fluoxetine (neutral/basic drug) was not detected in any samples, while acetaminophen (acidic drug) was detected at only two sites, and sulfapyridine (sulfonamide antibiotic) was detected at only one site. Sulfamethoxazole and carbamazepine were present at the highest maximum concentrations of 578 ng/L and 106 ng/L, respectively. The concentrations of most of the target pharmaceutically active compounds observed in surface water samples within the watershed were generally consistent with the number of people in urban centers near the sampling sites when compared with other studies in urban watersheds. However, carbamazepine, naproxen, and sulfamethoxazole were present at surprisingly high concentrations for some of the low density areas. Overall, these results demonstrate that pharmaceuticals are distributed in surface waters within a watershed in Quebec at concentrations similar to levels observed in previous studies done in other parts of North America.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 it