Response of cranberry and kidney beans to linuron
Bibliographic record
Abstract
Field studies were conducted in 2009 and 2010 at the Huron Research Station, Exeter, Ontario and the University of Guelph Ridgetown Campus, Ridgetown, Ontario to determine the tolerance of four cultivars of cranberry bean (“Etna”, “Hooter”, “SVM Taylor”, and “Capri”) and four cultivars of kidney bean (“Red Hawk”, “Pink Panther”, “Calmont”, and “Majesty”) to linuron applied preemergence at 1125 and 2250 g·ai·ha-1. One week after emergence (WAE), linuron applied PRE caused 0.4% to 1.2% injury in “Etna”, “Hooter”, “SVM Tayler”, and “Capri” cranberry bean and 3.1% to 3.6% injury in “Red Hawk”, “Pink Panther”, “Calmont”, and “Majesty” kidney bean. At 2 and 4 WAE, there was no difference in injury among the dry bean cultivars. Contrast comparing injury due to linuron in cranberry vs kidney bean cultivars indicated 2.3%, 1.7%, and 1.2% greater injury in kidney bean compared to cranberry bean at 1, 2, and 4 WAE, respectively. Linuron PRE caused slightly greater injury in kidney bean compared to cranberry bean but crop injury was minimal with no adverse effect on plant height, shoot dry weight, seed moisture content, and yield under the environments evaluated. Based on this research, linuron applied PRE at the proposed rate of 1125 g·ai·ha-1 can be safely used in cranberry and kidney beans 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".