Volunteer wheat (Triticum aestivum L.) competition and control in corn (Zea mays L.)
Bibliographic record
Abstract
Fifteen field experiments were conducted over a two-year period (2006-2007) at four Ontario locations to evaluate volunteer wheat competitiveness and efficacy of five post-emergence herbicides for control of volunteer wheat in corn. The level of competitiveness was dependent on the density of volunteer wheat. Volunteer wheat competition in corn reduced the emergence of corn leaf collars. Furthermore, volunteer wheat competition reduced total leaf area, leaf dry weight, shoot dry weight, plant and ear height and yield by 5% at densities of 2.8 to 6.0 plants m-2. Foramsulfuron, nicosulfuron, nicosulfuron/rimsulfuron provided greater than 70% control of volunteer cereals, while primisulfuron and rimsulfuron provided greater than 60% control. Volunteer cereal control with early and late application was greater than 82 and 61%, respectively. Hard red winter wheat control ranged from 84 to 93%, soft red and soft white winter wheat control ranged from 76 to 87%, and fall rye control was 56 to 71% at 56 days after treatment. Early herbicide application resulted in improved control of volunteer cereals and higher corn yield.
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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".