Control of common cocklebur (<i>Xanthium strumarium</i> L.) with pre- and postemergence herbicides in soybean
Bibliographic record
Abstract
Field trials were conducted in 2006 and 2007 on three Ontario farms with heavy infestations of cocklebur to determine the effectiveness of various preemergence (PRE) and postemergence (POST) herbicides for control of cocklebur in soybean [Glycine max (L.) Merr.]. There was minimal injury (2% or less) to soybean from the PRE and POST herbicides evaluated. Cloransulam applied PRE provided up to 98% visual control, reduced density 93%, and reduced dry weight of cocklebur 96%. Linuron, metribuzin, imazethapyr, and clomazone applied PRE provided 0 to 77% control and reduced density and dry weight of cocklebur minimally (54% or less) compared with the weedy check. Cloransulam applied POST provided as much as 98% control, reduced density up to 96%, and reduced dry weight of cocklebur as much as 98%. Chlorimuron, imazethapyr, imazethapyr plus bentazon, and glyphosate applied POST provided 49 to 90% control, reduced density 62 to 89%, and reduced dry weight of cocklebur 69 to 92%. Acifluorfen, fomesafen, bentazon, and thifensulfuron applied POST provided 1 to 51% control, reduced density 0 to 80%, and reduced dry weight 0 to 74% compared with the weedy check. Soybean yield increased as much as 79% compared with the weedy check as a result of cloransulam applied PRE or POST. Based on these results, cloransulam applied PRE or POST provides excellent control of cocklebur in soybean. Key words: Cocklebur, weed control, soybean, preemergence herbicide, postemergence herbicide
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".