Metolachlor and Atrazine in the Great Lakes
Bibliographic record
Abstract
Concentrations of atrazine and metolachlor and stereoisomer fractions (SF = herbicidally active/total stereoisomers) of metolachlor were determined in 101 surface water samples collected from the five Laurentian Great Lakes in 2005-2006. Geometric mean (GM) concentrations of atrazine ranged from 5.5 to 61 ng L(-1), decreasing from lakes Ontario approximately Michigan approximately Erie > Huron > Superior, while metolachlor concentrations ranged from 0.28 to 14 ng L(-1) and showed similar trends among the lakes. Median SFs ranged from 0.527 (Superior) to 0.844 (Erie) with an overall value of 0.708, and were significantly different among the Great Lakes (p < 0.05), except for Michigan vs Huron and Michigan vs Ontario. The SF in Erie was closest to that of the dominant product in use, S-metolachlor (SF = 0.880), while Superior showed an SF similar to that of racemic metolachlor (SF = 0.500). The median SFs in lakes Ontario, Huron and Erie were significantly lower than the median SF in Ontario stream samples collected in 2006-2007. The lower SFs in lakes suggest in-lake stereoselective processing of metolachlor or hold-up of older racemic metolachlor residues.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".