Temporal and Spatial Trends of Organochlorine Pesticides in Great Lakes Precipitation
Bibliographic record
Abstract
Organochlorine pesticide concentrations in precipitation samples collected from 1997 to 2003 at seven Integrated Atmospheric Deposition Network sites around the Great Lakes are reported. The 28-day volume weighted mean concentrations of several pesticides, including gamma-hexachlorocyclohexane (HCH), endosulfan, hexachlorobenzene, chlordane, and DDE, showed significant seasonal trends. For current-use pesticides (endosulfan and gamma-HCH), their concentrations peaked in late spring to summer just after their agricultural application. For the banned pesticides, higher concentrations were observed in the winter due to their enhanced partitioning to particles and scavenging by snow. Long-term decreasing trends were observed for several pesticides such as gamma-HCH and DDE. On the other hand, beta-HCH showed significant increasing concentrations as a function of time at Brule River, Eagle Harbor, and Sleeping Bear Dunes. Generally, Chicago had the highest concentration of chlordanes, dieldrin, and DDT, indicating that urban areas could be a source for these compounds to precipitation. For gamma-HCH and endosulfans, Point Petre had the highest concentrations due to the application of these pesticides in the surrounding areas.
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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 | 0.000 | 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) | 0.000 | 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".