Management of Spreading Dogbane (<i>Apocynum androsaemifolium</i>) in Wild Blueberry Fields
Bibliographic record
Abstract
Spreading dogbane is a troublesome weed of wild blueberry fields. Field studies were conducted in 2008 and 2009 to evaluate efficacy of different herbicides and application techniques on spreading dogbane as well as blueberry tolerance. Results indicated that summer-broadcast nicosulfuron at 25 g ai ha −1 with 0.5% v/v blend of surfactant with petroleum hydrocarbons suppressed (> 60%) spreading dogbane at three of four sites. Spot sprays with dicamba at 1 kg ae ha −1 effectively controlled (> 80%) spreading dogbane with minimal (19 to 23%) blueberry damage at three of four sites. Glyphosate spot sprays at 5 g ae L −1 water provided more effective and longer control than hand pulling. Wiping with glyphosate at 154 g ae L −1 water or wiping triclopyr at 29 g ae L −1 water onto the shoots is also an effective control method for localized patches of spreading dogbane. Although low to moderate crop damage may accompany these techniques, it may still be tolerable for growers to apply these options to limit long-term yield loss caused by spreading dogbane.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 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".