Effect of Halosulfuron Applied Preplant Incorporated, Preemergence, and Postemergence on Dry Bean
Bibliographic record
Abstract
Five field trials were conducted over a 2-yr period (2007, 2008) at various locations in Ontario to evaluate the tolerance of black, cranberry, kidney, otebo, pink, pinto, small red Mexican (SRM), and white bean to halosulfuron applied PPI, PRE, and POST at 35 and 70 g ai/ha. There was minimal injury (3% or less) with halosulfuron applied PPI or PRE in dry bean. At Exeter and Ridgetown, halosulfuron applied POST at 35 and 70 g/ha caused 3 to 5% and 4 to 8% injury in dry bean, respectively at 1 wk after herbicide application (WAA). The injury was transient with no significant injury at 2 and 4 WAA. At Harrow, halosulfuron POST at 35 and 70 g/ha caused as much as 4% injury at 35 g/ha and 14% injury at 70 g/ha in dry bean. Halosulfuron applied PPI, PRE, and POST at 35 and 70 g/ha caused no decrease in plant height of dry bean except for kidney bean, which was reduced 6% at 70 g/ha, and white bean, which was reduced 3% at both 35 and 70 g/ha. Halosulfuron applied PPI, PRE, and POST at 35 and 70 g/ha caused no decrease in dry bean yield except for kidney bean, which was reduced 9% at 35 g/ha and 10% at 70 g/ha; otebo bean, which was reduced 3% at 70 g/ha; and white bean, which was reduced 7% at both 35 and 70 g/ha. On the basis of these results, there is an adequate margin of crop safety in dry bean to halosulfuron applied PPI or PRE at 35 and 70 g/ha. In addition, there is an adequate margin of crop safety in black, cranberry, pink, pinto, and SRM bean to halosulfuron applied POST at 35 and 70 g/ha. However, further research is required to ascertain the tolerance of kidney, otebo, and white bean to halosulfuron applied POST.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".