Response of pinto and small red Mexican beans (<i>Phaseolus vulgaris</i> L.) to preplant‐incorporated herbicides
Bibliographic record
Abstract
Four field trials were conducted over a 2 year period at Exeter (2005, 2006), Harrow (2006), and Ridgetown (2006), Ontario, Canada, to evaluate the tolerance of pinto and small red Mexican (SRM) beans to the preplant‐incorporated (PPI) application of trifluralin, dimethenamid, S‐metolachlor, KIH‐485, imazethapyr, and flumetsulam. All the treatments, including the untreated control, were maintained weed‐free during the growing season. The PPI application of trifluralin, dimethenamid, and S‐metolachlor resulted in minimal transient visual injury, with no adverse effect on the plant height, shoot dry weight, seed moisture content, and yield of the pinto and SRM beans. The PPI application of imazethapyr and flumetsulam, especially at the high rate, initially caused 13% injury and reduced the plant height and shoot dry weight by 15 and 28%, respectively, but these injuries were transient and had no effect on the seed maturity and yield of the pinto and SRM beans. The PPI application of KIH‐485 caused 80% injury to the pinto and SRM beans and reduced the plant height, shoot dry weight, and yield. The dry bean maturity was also delayed. Based on these results, trifluralin, dimethenamid, S‐metolachlor, imazethapyr, and flumetsulam, applied as PPI herbicides, have the potential to be used in a weed management program for pinto and SRM beans. However, KIH‐485, applied as a PPI herbicide at the doses evaluated, does not have an adequate margin of crop safety for use in pinto and SRM bean production in Ontario.
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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".