Sweet Corn Hybrid Responses to Thifensulfuron-methyl
Bibliographic record
Abstract
Limited information exists on sweet corn ( Zea mays ) tolerance to postemergence (POST) applications of thifensulfuron-methyl under Ontario growing conditions. Eight sweet corn hybrids were evaluated for tolerance to thifensulfuron-methyl in four field experiments conducted in 2003 and 2004. Thifensulfuron-methyl was applied POST at 6 and 12 g·ha –1 a.i., the registered and twice the registered rate for use in soybean in Ontario. Sweet corn hybrid responses to thifensulfuron-methyl varied. Delmonte 2038 was the most sensitive to thifensulfuron-methyl and had as much as 92% visual injury, 76% height reduction, and 98% yield reduction compared to the nontreated control. Empire, GH1861, GH2298, and GH2684 hybrids showed visual injury of 53%, 55%, 53%, and 61%, height reduction of 34%, 31%, 32%, and 26% and yield reduction of 77%, 68%, 68%, and 51%, respectively. GG214, GH2547, and GSS9299 sweet corn hybrids were not as sensitive to thifensulfuron-methyl. The initial sensitivity observed in these hybrids was minimal and transient with no effect on yield. Although thifensulfuron-methyl is safe for use on some sweet corn hybrids, it has the potential to cause severe crop injury and yield reduction in other hybrids and therefore it should not be recommended for weed management in sweet corn production 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) | 0.000 | 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) | 0.001 | 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".