Weed economic thresholds : Useful agronomic tool or pipe dream?
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
Interest in more rational and objective approaches to weed management has increased considerably in Canada and elsewhere. Cost/benefit issues, environmental concerns, and the development of weed resistance to herbicides have cast doubt on the rationality and sustainability of prophylactic herbicide use. The concept of an economic threshold for weeds and the broader concept of integrated weed management have considerable potential as practical agronomic tools in Canadian crop production Systems. A large number of experiments have been conducted to determine the impact of weeds on crop yield, but the models developed from these studies have been put to little practical use. Constraints to the practical implementation of these concepts include a lack of realistic sampling procedures to assess the impact of weeds on crops over large areas, and a lack of information on the long-term implications of seed production by uncontrolled weeds. Weed ecologists conducting weed interference experiments should define their objectives better, and should provide guidelines on how their findings can be used at the farm level. Emphasis should be placed on the effects of the crop on the weed rather than the weed on the crop. There is also a need for greater coordination of research activities among weed ecologists. The establishment of standard protocols for long-term studies across locations and years would enhance the relevance and precision of weed interference models, and lead to the development of user- friendly decision support Systems specifically adapted to aiding rational weed management decisions in Canadian crop production Systems. The development of such Systems will be essential to the implementation of weed thresholds and integrated weed management.
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 | 0.000 |
| 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) | 0.002 | 0.001 |
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