Control of glyphosate resistant Canada fleabane with saflufenacil plus tankmix partners in soybean
Bibliographic record
Abstract
Six field trials were conducted over a two-year period (2014, 2015) to determine the level and consistency of glyphosate-resistant (GR) Canada fleabane control with glyphosate plus saflufenacil plus a third tankmix partner. GR Canada fleabane interference reduced soybean yield 73% compared with the weed free control. At 4 and 8 weeks after application (WAA), glyphosate plus saflufenacil provided 99% and 88% control of GR Canada fleabane respectively, and at 8 WAA, reduced GR Canada fleabane density by 96% and biomass by 89%. Glyphosate plus saflufenacil plus dicamba improved the control of GR Canada fleabane to 100% and 97% at 4 and 8 WAA, respectively. At 8 WAA, glyphosate plus saflufenacil plus amitrole reduced GR Canada fleabane density and biomass 99% and 97%, respectively. At 8 WAA, glyphosate plus saflufenacil plus dicamba at 300 or 600 g a.i. ha −1 reduced GR Canada fleabane biomass 97% and 98%, respectively. Tank-mixing dicamba with glyphosate plus saflufenacil applied pre-plant improved control of GR Canada fleabane; however, this caused 14% and 46% crop injury at 2 and 4 WAA, respectively. Soybean yield for saflufenacil alone and saflufenacil tankmix treatments were similar to the weed free control, with the exception of dicamba (600 g a.i. ha −1 ).
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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 | 0.001 | 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".