Opportunities and challenges for harvest weed seed control in global cropping systems
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
The opportunity to target weed seeds during grain harvest was established many decades ago following the introduction of mechanical harvesting and the recognition of high weed-seed retention levels at crop maturity; however, this opportunity remained largely neglected until more recently. The introduction and adoption of harvest weed seed control (HWSC) systems in Australia has been in response to widespread occurrence of herbicide-resistant weed populations. With diminishing herbicide resources and the need to maintain highly productive reduced tillage and stubble-retention practices, growers began to develop systems that targeted weed seeds during crop harvest. Research and development efforts over the past two decades have established the efficacy of HWSC systems in Australian cropping systems, where widespread adoption is now occurring. With similarly dramatic herbicide resistance issues now present across many of the world's cropping regions, it is timely for HWSC systems to be considered for inclusion in weed-management programs in these areas. This review describes HWSC systems and establishing the potential for this approach to weed control in several cropping regions. As observed in Australia, the inclusion of HWSC systems can reduce weed populations substantially reducing the potential for weed adaptation and resistance evolution. © 2017 Society of Chemical Industry.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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