Symposium Introduction to the symposium on Weed ecology in long-term experiments: status and future needs
Bibliographic record
Abstract
The need for long-term agricultural research is generally recognized. However, most long-term experiments have been designed to evaluate effects of fertility and crop rotation. Much of the current research in weed biology and weed management is conducted on a short-term basis that does not address adequately the long-term aspects of weed population ecology. In recent decades, a number of long-term experiments have been initiated to investigate the effects of both agronomic and weed management practices on weed communities. Knowledge of the existence of these experiments and the information being obtained from them are not always readily available. The Symposium held at the 2002 WSSA annual meeting in Reno, Nevada, had several goals: (1) to provide WSSA members, and other researchers, with information about long-term experiments that are currently ongoing, or recently terminated, that are investigating weed ecology and weed management; (2) to provide an exchange of ideas between researchers involved in long-term weed ecology research; (3) to provide examples of protocols and problems associated with conducting long-term weed ecology research; (4) to evaluate the scientific principles that have been, or may be, added to the discipline of weed science; and (5) to provide funding agencies with examples of how long-term weed management experiments clarify impacts of weeds in relation to sustainable agriculture.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.039 | 0.015 |
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 source (direct Gemma or distilled Codex), 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".