Linuron Biologically Effective Dose for Glyphosate-Resistant Giant Ragweed (<i>Ambrosia trifida</i> L.) Control in Soybean (<i>Glycine max</i> L.)
Bibliographic record
Abstract
Glyphosate-resistant (GR) giant ragweed (Ambrosia trifida L.) was first identified in Canada in 2008 and has since been found throughout southwestern Ontario. Six field trials were conducted over a two-year period (2012, 2013) on Ontario farms with GR giant ragweed to evaluate the efficacy of linuron applied pre-plant (PP) in soybean (Glycine max (L.) Merr.). The dose required for 50%, 80%, and 95% GR giant ragweed control was 1238, 2959, and 6018 g·ai·ha-1 four weeks after application (WAA), respectively. The linuron dose needed for 50%, 80%, and 95% reduction in density was 1554, 3181, and 5643 g·ai·ha-1 and 1204, 2496, and 4452 g·ai·ha-1 for dry weight, respectively. Application of 7874 g·ai·ha-1 linuron was needed to obtain soybean yields that were 90% of the weed-free control; approximately 3.5 times the maximum field recommended dose. To achieve 95% and 98% yields, greater than 8640 g·ai·ha-1 linuron was required. Application of linuron plus glyphosate PP in soybean will help to control GR giant ragweed as well as reduce GR selection pressure.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".