Evaluation of foramsulfuron for poverty oat grass [<i>Danthonia spicata</i> (L.) P. Beauv. ex Roem. & Schult.] and rough bentgrass (<i>Agrostis scabra</i> Willd.) management in lowbush blueberry (<i>Vaccinium angustifolium</i> Ait.)
Bibliographic record
Abstract
The susceptibility of poverty oat grass and rough bentgrass to foramsulfuron was assessed in greenhouse and field experiments. A dose response study was conducted in a greenhouse with treatments consisting of 0, 4.4, 8.8, 17.5, 35, 70, 140, and 280 g foramsulfuron ha−1. Field experiments were conducted using a similar dose response and also included industry standard fluazifop-P-butyl and sethoxydim applications. Foramsulfuron application rates of 4.04 ± 0.73 and 6.6 ± 1.3 g a.i. ha−1 reduced poverty oat grass biomass by 50% in the greenhouse. In contrast, 4.4 g a.i. ha−1 foramsulfuron caused >70% reduction in rough bentgrass biomass in the greenhouse. In the field, 280 g a.i. ha−1 of foramsulfuron was required to reduce poverty oat grass total and flowering tuft density and >35 g a.i. ha−1 (registered foramsulfuron rate) was required to reduce flowering tuft inflorescence number by 50%. In contrast, rough bentgrass was injured by 4.4 and 8.8 g a.i. ha−1 of foramsulfuron and total and flowering tuft density and flowering tuft inflorescence number were reduced by all other foramsulfuron rates evaluated. Foramsulfuron application rates of 13.1 ± 2.4, 10.3 ± 1.2, and 5.4 ± 0.9 g a.i. ha−1 reduced rough bentgrass total tuft density, flowering tuft density, and tuft inflorescence number, respectively, by 50%. Lowbush blueberry growers can consider foramsulfuron for postemergence management of rough bentgrass, but additional research is required to identify new herbicides for postemergence poverty oat grass management.
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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 | 0.001 |
| 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".