Response of Nebraska Horseweed (Conyza canadensis) Populations to Dicamba
Bibliographic record
Abstract
Dicamba-resistant soybeans are being developed to provide an additional herbicide mechanism-of-action for postemergence weed control in soybean. Numerous broadleaf species, including horseweed, have evolved resistance to glyphosate. It is anticipated that dicamba will be used by farmers as a primary tool to manage these weeds. Studying and understanding variability in horseweed response to dicamba will aid in developing appropriate risk management strategies to extend the utility of the dicamba-resistance technology. Horseweed plants from ten Nebraska populations were treated with one of nine doses of dicamba in greenhouse experiments. At 28 days after treatment (DAT) visual injury estimations were made and plants were harvested to determine dry weight. There was a three-fold difference in the I90 (90% visual injury estimate) between the least (638 g ha-1) and most (205 g ha-1) susceptible populations. Two plants from five populations were observed for an additional three months. No plants treated at doses above 280 g ha-1 survived to set seeds. These results suggest that maintaining use doses of 560 g ha-1 or greater may fully control horseweed populations from Nebraska and minimize the risk of plants surviving to set seed, in addition to practicing other proven herbicide-resistance management strategies.
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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) | 0.000 | 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 | 0.000 |
| 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".