Response of dry bean to Group 15 herbicides applied preplant incorporated
Bibliographic record
Abstract
A study consisting of four field experiments was conducted over a 2-yr period (2016, 2017) near Exeter and Ridgetown, ON, to compare the tolerance of adzuki, kidney, small red, and white beans to four Group 15 herbicides including pethoxamid (1200 and 2400 g a.i. ha −1 ), S-metolachlor (1600 and 3200 g a.i. ha −1 ), dimethenamid-P (693 and 1386 g a.i. ha −1 ), and pyroxasulfone (100 and 200 g a.i. ha −1 ) applied preplant incorporated (PPI). At 1 wk after emergence (WAE), pethoxamid, S-metolachlor, dimethenamid-P, and pyroxasulfone caused as much as 22%, 17%, 38%, and 15% adzuki bean injury, respectively. The injury decreased with time; at 8 WAE, pethoxamid, S-metolachlor, dimethenamid-P, and pyroxasulfone applied PPI caused as much as 3%, 4%, 12%, and 7% adzuki bean injury, respectively. The injury was lower in other market classes of dry bean. At 1, 2, and 4 WAE, pethoxamid, S-metolachlor, dimethenamid-P, and pyroxasulfone caused as much as 4%, 2%, 4%, and 14% injury in kidney bean, 3%, 2%, 4%, and 12% injury in small red bean, and 5%, 3%, 6%, and 13% injury in white bean, respectively. However, the injury at 8 WAE was 5% or less in kidney, small red, and white beans with all Group 15 herbicides evaluated. Based on this research, pyroxasulfone was the most injurious to dry beans, it reduced plant height as much as 15% and seed yield as much as 17%. The Group 15 herbicides evaluated were more injurious to adzuki bean than kidney, small red, or white beans.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".