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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".