Integrated management of scouringrush (<i>Equisetum hyemale</i>)
Bibliographic record
Abstract
Scouringrush ( Equisetum hyemale L.) is an increasing problem in some fields. The objective of this research was to identify effective chemical and cultural methods for controlling scouringrush. A field experiment was conducted at three locations in southeastern Nebraska. Five herbicides (chlorsulfuron, dichlobenil, metsulfuron, MCPA, and triclopyr) were applied using a backpack sprayer, and were compared to competition with corn ( Zea mays L), repeated tillage, and repeated mowing. One year after treatments were applied, chlorsulfuron (158 g a.i. ha−1) reduced scouringrush biomass 100% and dichlobenil (6700 g ha−1) reduced biomass 70%. Repeated tillage or competition from a dense stand of corn reduced scouringrush biomass approximately 50%. Repeated mowing did not reduce scouringrush stem count or biomass. A greenhouse study was conducted to determine the effect of chlorsulfuron on corn and soybean ( Glycine max (L.) Merr.) growth when applied at rates necessary to control scouringrush. Both foliar- and soil-applied chlorsulfuron reduced corn and soybean biomass. Chlorsulfuron was the only treatment that completely controlled scouringrush but will have an adverse effect on corn and soybean growth.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".