Tillage and Planting Options for Unintended Corn Following Wheat Cover
Bibliographic record
Abstract
Tillage options for corn planted after frozen wheat have to be considered in light of trying to make the best out of a challenging situation. Some of the unique features about trying to establish corn into wheat versus soybean or corn stubble from the previous year are that wheat may have negatively affected the soil physical (moisture and temperature) and chemical (nitrogen availability and potential allelopathic substances) environment for corn. Just how well corn will perform depends on the quantity of wheat biomass cover, soil conditions, and the weather conditions following wheat kill or incorporation and subsequent corn planting. We don’t have much experience with spring tillage options for corn following wheat cover crops, but we know from previous research with corn following wheat and rye cover crops in Ontario (Raimbault et al., 1990; Raimbault et al., 1991; Tollenaar et al., 1993) that there are some things we can do to help corn get off to a good start. Our recommendations are as follows: 1. Early Kill for No-till Corn. If you are intending on no-till, chemically kill the wheat as soon as the decision has been made to plant the field to corn. Early kill
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".