Current-use pesticides in inland lake waters, precipitation, and air from Ontario, Canada
Bibliographic record
Abstract
Concentrations of current-use pesticides (CUPs) in water, zooplankton, precipitation, and air samples as well as stereoisomer fractions (SF; herbicidally active/total stereoisomers) of metolachlor were determined in water samples collected from 10 remote inland lakes in Ontario, Canada, between 2003 and 2005. The most frequently detected chemicals in lake water, precipitation, and air were α-endosulfan, atrazine, metolachlor, chlorpyrifos, chlorothalonil, and trifluralin, and α-endosulfan and chlorpyrifos were the chemicals detected frequently in zooplankton. Air concentrations of these CUPs were within the range of previously reported values for background sites in the Great Lakes basin. High detection frequency of CUPs in lake water and precipitation was attributed to high usage amounts, but some CUPs such as ametryn and disulfoton that were not used in Ontario were also detected. Mean bioaccumulation factors (wet wt) in zooplankton for endosulfan ranged from 160 to 590 and from 20 to 60 for chlorpyrifos. The overall median SF of metolachlor in precipitation samples (0.846) was similar to that of the commercial S-metolachlor (0.882). However, the median SF of metolachlor in water from all sampled inland lakes (0.806) was significantly lower compared with Ontario rivers (0.873) but higher compared with previous measurements in the Great Lakes (0.710). Lakes with smaller watershed areas showed higher SFs, supporting the hypothesis of stereoselective processing of deposited metolachlor within the watersheds, followed by transport to the lakes.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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 teacher head, 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".