Atrazine Accentuates Carryover Injury from Mesotrione in Vegetable Crops
Bibliographic record
Abstract
Trials were established in 2003, 2004, and 2005 in Ontario to determine the effects of residues of mesotrione, atrazine, and mesotrione plus atrazine 1 and 2 yr after application on broccoli, carrot, cucumber, onion, and potato. One yr after mesotrione application, injury was 43, 37, 18, 24, and 0% in broccoli, carrot, cucumber, onion, and potato, respectively. The addition of atrazine to mesotrione in the year before planting increased injury to 55, 53, 30, 42, and 3% in broccoli, carrot, cucumber, onion, and potato, respectively. Plant dry weight and yield were also decreased by mesotrione residues the year after application in all crops except potato. The addition of atrazine to mesotrione accentuated the reduction in dry weight and yield in broccoli, carrot, cucumber, and onion. There was no injury, or reductions in dry weight or yield in any crop planted 2 yr after application of mesotrione alone or in tank mix with atrazine. A recropping interval of 2 yr is recommended following applications of mesotrione or mesotrione plus atrazine for broccoli, carrot, cucumber, and onion. Potato can be safely planted the year following application of mesotrione plus atrazine.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".