Tolerance of three types of winter wheat (<i>Triticum aestivum</i> L.) to fluroxypyr plus MCPA ester
Bibliographic record
Abstract
Six field trials were conducted over a 3-yr period (2005-2007) near Exeter and Ridgetown, Ontario, to evaluate the tolerance of three types of winter wheat [soft white (SWWW), soft red (SRWW) and hard red (HRWW)] to three rates of fluroxypyr plus MCPA ester (54 + 281.25 g a.i. ha-1; 108 + 562.5 g a.i. ha-1; 216 + 1125 g a.i. ha-1) at two postemergence (POST) application timings [Zadoks 31-32 (POST 1) and Zadoks 33-34 (POST 2)] in the spring. Fluroxypyr plus MCPA ester applied at POST 1 caused no injury to winter wheat. Fluroxypyr plus MCPA ester applied at POST 2 caused as much as 4, 4 and 7% injury 14 d after treatment (DAT) in SWWW, SRWW and HRWW, respectively. Fluroxypyr plus MCPA ester applied at 54 + 281.25 g a.i. ha-1, 108 + 562.5 g a.i. ha-1 and 216 + 1125 g a.i. ha-1 at POST 2 caused up to 1, 6 and 10% injury 14 DAT, respectively. Fluroxypyr plus MCPA ester applied at 216 + 1125 g a.i. ha-1 (POST 2) caused as much as 5, 5 and 12% injury in SWWW, SRWW and HRWW, respectively. Winter wheat height was reduced an average of 3 cm with the high rate of fluroxypyr plus MCPA ester in 2006. There was no significant effect of fluroxypyr plus MCPA ester rate or application timing on the yield of winter wheat. This study concludes that there is an adequate margin of crop safety in winter wheat to fluroxypyr plus MCPA ester applied POST in the spring.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".