Responses of Dry Bean to Biostimulants Added to Postemergence Herbicides
Bibliographic record
Abstract
The effect of biostimulants such as Crop Booster and RR SoyBooster on dry bean under Ontario environmental conditions is not known. A total of 12 field experiments (6 in cranberry bean “Etna” and 6 in white bean “OAC REX”) were conducted at two locations (Ridgetown and Exeter, Ontario, Canada) to evaluate the effect of Crop Booster and RR SoyBooster on visible injury, shoot dry weight, height and yield of cranberry and white bean. Visible injury ranged from 0% to 7.3% in white bean and 0% to 9.4% in cranberry bean with quizalofop-p-ethyl, bentazon, fomesafen, bentazon plus fomesafen, imazethapyr and imazethapyr plus bentazon alone or in combination with Crop Booster and RR SoyBooster. The addition of Crop Booster or RR SoyBooster to herbicides evaluated had no significant effect on shoot dry weight, height, seed moisture content and yield of white or cranberry bean except with the addition of RR SoyBooster to quizalofop-p-ethyl which increased height 3.7% and the addition of the Crop Booster to bentazon which decreased shoot dry weight 12% and the addition of Crop Booster to bentazon plus fomesafen which increased shoot dry weight 17% in white bean. Based on these results, there were minimal effects from the addition of Crop Booster or RR SoyBooster to commonly used herbicides in white and cranberry bean.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".