Changes in Acid Herbicide Concentrations in Urban Streams after a Cosmetic Pesticides Ban
Bibliographic record
Abstract
Surface water concentrations of the acid herbicides 2,4-D, dicamba and mecoprop were measured in ten urban Ontario streams before (2003–2008) and after (2009–2012) a ban on the sale and use of pesticides for cosmetic (non-essential) purposes. Frequencies of detection (2003–2012) were 98%, 96% and nearly 100%, respectively for 2,4-D, dicamba and mecoprop. Concentrations were typically in the ng L−1 range, although periodic spikes in the µg L−1 range were observed. Concentrations in a majority of the study streams decreased significantly following the cosmetic pesticides ban. Concentrations decreased from 16% to 92% depending on the stream and herbicide. The presence of these herbicides in urban streams was likely a result of urban applications. Concentrations were significantly related to population density or urban land cover, and the relative proportion of the three herbicides observed in urban stream water approximated the ratios found in pesticide products formulated for urban use. Longer-term trends indicate that decreases in stream water herbicide concentrations may have preceded the ban and may be related to increased public awareness of pesticide issues and voluntary reductions in urban pesticide use.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".