Biologically effective rate of halosulfuron applied postemergence in corn
Bibliographic record
Abstract
There is little information on the biologically effective rate of halosulfuron applied after emergence (postemergence, POST) for the control of broadleaf weeds in corn under Ontario environmental conditions. Six field trials were conducted over a 2-yr period (2014–2015) to determine the biologically effective rate of halosulfuron applied POST for the control of velvetleaf, pigweed species, common ragweed, common lambsquarters, and eastern black nightshade in corn. Based on regression analysis, the predicted halosulfuron rates required to cause 5%, 10%, and 20% corn injury were 53, 138, and >560 g a.i. ha−1 at 1 week after application (WAA), 109, 276, and >560 g a.i. ha−1 at 2 WAA, and 493, >560, and >560 g a.i. ha−1 at 4 WAA, respectively. The predicted halosulfuron rates applied POST for 95% control of velvetleaf, pigweed species, common ragweed, common lambsquarters, and eastern black nightshade were 10–13, 35–143, 25–57, >560, and >560 g a.i. ha−1, respectively. The predicted halosulfuron rates applied POST to reduce velvetleaf, pigweed species, common ragweed, and common lambsquarters density by 80% were 9, 9, 7, and >560 g a.i. ha−1, respectively. The predicted halosulfuron rates applied POST to reduce velvetleaf, pigweed species, and common ragweed dry weight by 80% were 2, 3, and 2 g a.i. ha−1, respectively. Based on these results, halosulfuron applied POST at the registered rate of 34–68 g a.i. ha−1 has the potential to control velvetleaf, pigweed species, and common ragweed but does not adequately control common lambsquarters and eastern black nightshade in corn.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".