Occurrence and management of herbicide resistance in annual vegetable production systems in North America
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Herbicide resistance has been studied extensively in agronomic crops across North America but is rarely examined in vegetables. It is widely assumed that the limited number of registered herbicides combined with the adoption of diverse weed management strategies in most vegetable crops effectively inhibits the development of resistance. It is difficult to determine whether resistance is truly less common in vegetable crops or whether the lack of reported cases is due to the lack of resources focused on detection. This review highlights incidences of resistance that are thought to have arisen within vegetable crops. It also includes situations in which herbicide-resistant weeds were likely selected for within agronomic crops but became a problem when vegetables were grown in sequence or in adjacent fields. Occurrence of herbicide resistance can have severe consequences for vegetable growers, and resistance management plans should be adopted to limit selection pressure. This review also highlights resistance management techniques that should slow the development and spread of herbicide resistance in vegetable crops.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 it