Responses of Four Types of Winter Wheat to Fenoxaprop-p-ethyl
Bibliographic record
Abstract
Fenoxaprop-p-ethyl is a selective grass herbicide that if registered will provide winter wheat growers with an additional weed control option. Field experiments were established in the fall of 2011, 2012 and 2013 at Ridgetown and Exeter, Ontario, to determine the sensitivity of four market classes of winter wheat [Soft white winter wheat (SWWW), soft red winter wheat (SRWW), hard white winter wheat (HWWW) and hard red winter wheat (HRWW)] to 1X and 2X fenoxaprop-p-ethyl/safener at early-(EPOST) or late-post emergence (LPOST) application timings. Fenoxaprop-p-ethyl/safener applied LPOST at 1X and 2X the manufacturer’s proposed label rate caused 4% and 5% injury 1 week after application (WAA), respectively. The injury observed was transient with 1% injury 2 WAA. Winter wheat height ranged from 91 to 95, 76 to 77, 76 to 79 and 90 to 93 cm while grain yield was 6.2 to 6.4, 6.1 to 7.1, 5.5 to 5.8 and 5.6 to 6.2 t?ha?1 for SWWW, SRWW, HRWW and HRWW, respectively. Exeter sites were not affected by fenoxaprop-p-ethyl/ safener treatment. At Ridgetown and Exeter, no market class-specific response was identified for the cultivars evaluated. Based on this study, fenoxaprop-p-ethyl/safener has the potential to cause only minor and transient injury in winter wheat that will not decrease yield. Furthermore, this research supports the registration of fenoxaprop-p-ethyl/safener for spring POST application in winter wheat in Ontario.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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 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".