Conventional vs. Glyphosate-Resistant Cropping Systems in Ontario: Weed Control, Diversity, and Yield
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
Glyphosate-resistant (GR) crops have been adopted rapidly since their commercial introduction, and with the increase in commercially available crops resistant to glyphosate, continuous use of the same herbicide mode of action is now possible in some crop rotations. A 6-yr study was initiated to investigate the effects of conventional herbicides compared with continuous use of glyphosate in GR or Roundup Ready corn and GR soybean in a corn–soybean and a corn–soybean–winter wheat rotation. Individual experiments were fully phased and established at three locations under conventional tillage (CT) and at two locations under no-tillage (NT). Results indicated that midseason weed ground cover was lower when weeds were controlled with glyphosate; however, in most cases, this did not result in improved corn or soybean yields. Within locations, species richness, which strongly influenced other diversity indicators, was most affected by the herbicide treatments. Including winter wheat in the crop rotation had little effect on corn and soybean weed ground cover, density, and community structure and only affected soybean yield. Moreover, no effects of herbicide system used in previous corn and soybean were observed in winter wheat, with the exception of species diversity in NT, where species diversity tended to be greater when weeds in previous corn and soybean were treated with conventional herbicides. After 6 yr, the effects of continuous use of GR crops in rotation were similar to those reported in previous studies; however, continued monitoring and longer-term investigations of these systems are necessary to detect the early stages of development of herbicide-resistant biotypes.
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 | 0.001 | 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