Environmental Concentrations of Agricultural Herbicides in Saskatchewan, Canada: Bromoxynil, Dicamba, Diclofop, MCPA, and Trifluralin
Bibliographic record
Abstract
Herbicides are the most commonly used group of agricultural pesticides on the Canadian Prairies and, in 1990, more than 20000 Mg of herbicides were applied in the provinces of Alberta, Saskatchewan, and Manitoba. The present paper reports on environmental concentrations of five herbicides currently used in the prairie region. The herbicides bromoxynil [3,5-dibromo-4-hydroxy-benzonitrile], dicamba [3,6-dichloro-o-anisic acid], diclofop [(RS)-2-[4-(2,4-dichlorophenoxy)-phenoxy]propanoic acid], MCPA [(4-chloro-2-methylphenoxy)acetic acid], and trifluralin [alpha,alpha,alpha-trifluoro-2,6-dinitro-N,N-isopropyl-p-toluidine] were measured in the atmosphere, bulk atmospheric deposits, surface film, and dugout (pond) water at two sites near Regina, Saskatchewan, during 1989 and 1990. All five herbicides were detected in air and surface film and all but trifluralin were detected in the bulk atmospheric deposits and dugout water. Trifluralin was most frequently detected in air (79% of samples) whereas bromoxynil was present in maximum concentration (4.2 ng m(-3)). MCPA was present in maximum levels in bulk atmospheric (wet plus dry) deposits (2350 ng m(-2) d(-1)), surface film (390 ng m(-2)), and dugout water (330 ng L(-1)), whereas dicamba was most frequently detected in surface film (47%) and dugout water (97%). The highest quantities of the herbicides tended to be present during or immediately after the time of regional application.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".