Control of Glyphosate-Resistant Giant Ragweed in Winter Wheat
Bibliographic record
Abstract
Four field experiments were conducted over a 2-yr period (2012 and 2013) in winter wheat to evaluate POST herbicides for the control of glyphosate-resistant (GR) giant ragweed. POST herbicides were evaluated for winter wheat injury and GR giant ragweed control, population density, and aboveground biomass. The herbicides used in this study provided 54 to 90% and 51 to 97% control of GR giant ragweed at 4 and 8 wk after treatment (WAT), respectively. At 8 WAT, auxinic herbicide treatments or herbicide tank mix/premix treatments that contained auxinics provided 78 to 97% control of GR giant ragweed. Reductions in GR giant ragweed population density and aboveground biomass were 62 to 100% and 83 to 100%, respectively, and generally reflected the level of control. The results of this research indicate that Ontario, Canada, corn and soybean growers should continue to incorporate winter wheat into their crop rotation as one component of an integrated weed management (IWM) strategy for the control of GR giant ragweed.
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.
How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".