Sources and Occurrence of Dacthal in the Canadian Atmosphere
Bibliographic record
Abstract
Dacthal is a herbicide that can undergo long-range atmospheric transport. Due to limited use in Canada, its occurrence in the Canadian environment is likely associated with transboundary flow from the United States where 100 times more dacthal is used. To investigate its atmospheric distribution and possible sources, two sampling strategies were applied. First, polyurethane foam-disk passive air samplers were deployed across the country from the spring to summer of 2004 and 2005. Results showed highest dacthal concentrations at two sites in southern Ontario (max: 50 pg m(-3)) and much lower concentrations in other agricultural regions across Canada. Second, daily high-volume air samples were collected at a field site in north Toronto (Downsview). Sampling at this site was triggered by real-time meteorological forecast models that indicated when air flow to the site originated in the United States. Two such events, one in late June and one in late September 2005, were sampled. In both cases, elevated dacthal concentrations were captured (e.g., up to 319 pg m(-3) in the June event) and they were well correlated with transboundary flow from the United States. Finally, the octanol--air partition coefficient (K(OA)) of dacthal and other current-use pesticides was measured. K(OA) was used to derive a particle--gas partitioning coefficient (K(p)) for dacthal (Log K(p) = -4.1), indicating that this compound should exist mainly in the gas phase.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".