Pharmaceuticals and other anthropogenic tracers in surface water: A randomized survey of 50 Minnesota lakes
Bibliographic record
Abstract
Water from 50 randomly selected lakes across Minnesota, USA, was analyzed for pharmaceuticals, personal care products, hormones, and other commercial or industrial chemicals in conjunction with the US Environmental Protection Agency's 2012 National Lakes Assessment. Thirty-eight of the 125 chemicals analyzed were detected at least once, all at parts per trillion concentrations. The most widely detected was N,N-diethyl-m-toluamide, present in 48% of the lakes sampled. Amitriptyline, a widely used antidepressant, was found in 28% of the lakes. The endocrine active chemicals bisphenol A, androstenedione, and nonylphenol were found in 42%, 30%, and 10% of the lakes, respectively. Cocaine was found in 32% of the lakes, and its degradation product, benzoylecgonine, was detected at 28% of the locations. Carbadox, an antibiotic used solely in the production of swine, was also present in 28% of the lakes sampled. The means by which these and other chemicals were transported to several of the remote lakes is unclear but may involve atmospheric transport.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".