Control of Glyphosate-Resistant Horseweed (<i>Conyza canadensis</i>) with Dicamba Applied Preplant and Postemergence in Dicamba-Resistant Soybean
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Herbicide-resistant crops, such as glyphosate-resistant (GR) soybean, allow for broad-spectrum, flexible weed control with minimal crop injury; however, the development of GR weeds, such as horseweed, has forced reliance on alternative herbicides for control of these weeds. While preplant (PP) herbicides provide excellent control of GR-horseweed, there are currently no POST herbicide control options within soybean. The objective of this study was to evaluate the efficacy of dicamba for the control of GR-horseweed when applied PP, POST, and sequentially in dicamba-resistant soybean. Dicamba applied PP at 600 g a.e. ha −1 provided 90 to 100% control of GR-horseweed 8 wk after application (WAA) across three field trials conducted in Ontario in 2011 and 2012. Similarly, sequential applications provided 91 to 100% control. This technology provides a much-needed POST option of dicamba to be applied as a rescue treatment to control weed escapes caused by late emergence or poor initial control following a PP herbicide application.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 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 it