Summary of Certified Crop Advisors’ Response to a Weed Resistance Survey
Bibliographic record
Abstract
Nearly 400 herbicide‐resistant weed biotypes due to one or several modes of action have been documented worldwide. Certified crop advisors (CCAs) were surveyed in December 2012 about the attitudes of clients toward resistant weeds and management. About 10% of total U.S. (∼1000 North Central, 60 Northeast, 165 West, and 257 South and Southeast regions) and Canadian (232) CCAs responded to the survey. Results were grouped by country, U.S. region, and job classification, with differences identified using χ 2 analysis. Twenty‐three percent of the South and Southeast regions CCAs identified the weed resistance level in their territory as “heavy,” whereas 5.5% identified the level as “epidemic,” compared with 0 in these categories for Canadian CCAs and CCAs in the U.S. Northeast and West regions. About 1% of CCAs in sales identified weed resistance as “epidemic,” compared with 5.6% of agriculture manufacturer representatives. Resistance management tactics listed frequently included multiple modes of action (20%), herbicide or crop rotation (16% each), and preemergence or residual herbicide application (14%), whereas integrated pest management was listed <2% of the time. In the South and Southeast regions, about 50% of the respondents thought that producers would modify current production practices “…only if the resistant weed were present in their fields,” whereas 37 and 31% of the North Central and Northeast/West regions, respectively, chose this answer. The cost of resistance implementation was seen as a primary barrier to implementation by 24% of the Northeast/West, North Central, and Canadian respondents. These findings suggest that solutions for weed resistance must be effective, easily implemented, and cost conscious to maximize acceptance and implementation by farmers.
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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 | 0.001 | 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 | 0.000 | 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 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".