Atmospheric Atrazine at Canadian IADN Sites
Bibliographic record
Abstract
Atrazine is one of the most widely used herbicides in North America and has been primarily applied to corn production in the Great Lakes basin for over 30 years. During 1996-2002, atrazine concentrations in the atmospheric gas and particle phases were investigated at three Canadian Integrated Atmospheric Deposition Network (IADN) sites including two lakeside sites (Burnt Island and Point Petre) and a rural inland site (Egbert). Strong seasonality with peak concentrations occurring in late April-early July was observed. An atrazine usage map for Canada (sum: 870 t) and the United States (sum: 34 500 t) in 2002 was created. Local application and regional atmospheric transport both appear to contribute to its atmospheric occurrence, while the latter might episodically result in high concentrations events. No strong temperature dependence was observed for atrazine particle-gas partitioning. Recent measurement results of atrazine in precipitation samples collected at Egbert and another agricultural site, Vineland, through the Canadian Atmospheric Network for Currently Used Pesticides (CANCUP), are also presented, Dry, wet, and gas exchange deposition all contribute to atmospheric inputs of atrazine to the Great Lakes. For Lake Ontario, gas exchange is estimated to be of similar magnitude to dry and wet deposition.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".