Multiple herbicide–resistant canola can be controlled by alternative herbicides
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
Unintentional herbicide resistance gene stacking in canola may alter the sensitivity of volunteers to herbicides of alternative modes of action commonly used for their control. Greenhouse experiments were conducted to investigate the response of three single-herbicide–resistant (HR) cultivars (glyphosate, glufosinate, imidazolinone), one non-HR cultivar, and seven multiple (double or triple)–HR experimental lines to 2,4-D (amine and ester), MCPA ester, and metribuzin applied at the two- to three-leaf stage and of one non-HR and four HR cultivars (glyphosate, glufosinate, imidazolinone, bromoxynil) to 2,4-D amine applied at two growth stages (two- to three-leaf stage and five- to six-leaf stage). All canola cultivars or lines treated at the two- to three-leaf stage responded similarly to increasing doses of each of the three herbicides. At the five- to six-leaf stage, however, the bromoxynil HR cultivar was less sensitive to 2,4-D than the other cultivars. The results of this study suggest that canola with multiple-herbicide–resistance traits does not differ from cultivars that are non-HR or single HR in its sensitivity to herbicides commonly used to control volunteers. All volunteers, whether non-HR, single HR, or multiple HR, should be treated when plants are most sensitive to herbicides (two- to four-leaf stage) to reduce their interference against crops and their perpetuation of gene flow.
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 | 0.001 |
| 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) | 0.000 | 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