Future Research Directions for Weed Science<sup>1</sup>
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
A Research Committee was established by the Weed Science Society of America to outline the direction of weed science research during the next decade. Weeds adversely affect humans in both agricultural and nonagricultural environments. It is the opinion of the research committee that weed science will be advantageously positioned for the future if research focuses on research decision processes, weed biology and ecology, weed control and management practices, herbicide resistance, issues related to transgenic plants, environmental issues, and potential benefits of weeds. These future weed science research directions endorse those of the commodity and grower input group Coalition for Research on Plant Systems (CROPS)'99, a U.S. Department of Agriculture (USDA)-supported initiative. The future of weed science is dependent on a joint effort from industry, government regulators, and the public sector consisting of grower groups, as well as USDA, Agriculture and Agri-Food Canada (AAFC), and university researchers. It is our opinion that efforts spent on these research areas will benefit not only growers, commodity groups, homeowners, and industry, but society at large, through the maintenance and improvement of the food and fiber production system, and the environment in North America.Abbreviations: AAFC, Agriculture and Agri-Food Canada; CROPS'99, Coalition for Research on Plant Systems (1999); EWRS, European Weed Research Society; GPS, global positioning systems; HRC, herbicide-resistant crops; IWM, integrated weed management; KBDSS, knowledge-based decision support strategies; USDA, U.S. Department of Agriculture; WSSA, Weed Science Society of America.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it