Velvetleaf (<i>Abutilon theophrasti</i>) Response to Glyphosate on the Field Edge
Bibliographic record
Abstract
Control of weeds growing around field edges to limit seed production is an important component of preventative weed management. POST herbicide rates that are effective on weeds growing within a dense corn or soybean canopy may not be high enough to control weeds at the edge of a field. A study was conducted from 2004 through 2006 to compare velvetleaf growth and fecundity at the edge of the field as opposed to within the crop in response to a range of glyphosate rates. Treatments included position (plot center or edge), time of emergence (VE or V4 crop growth stage) and glyphosate rate (0 to 900 g ae ha−1). Without herbicide application, velvetleaf plants grown on the edge flowered earlier, had thicker stems, and produced more seed capsules than plants grown in the center of the plots. At glyphosate application rates of 200 to 900 g ha−1, the percentage of plants surviving and reproducing was higher on the edge than within the crop. Edge plants treated with 900 g ha−1of glyphosate produced more seeds than center plants that received no herbicide. Dose–response curves were used to estimate the glyphosate rate that would reduce seed production of surviving plants to 80% of the untreated plants. Plants emerging at the VE stage were estimated to require 300 g ha−1within the corn or soybean canopy and 668 g ha−1on the crop edge, whereas plants emerging at the V4 stage would require 0 g ha−1within the canopy and 280 g ha−1on the crop edge.
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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) | 0.001 | 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".