Investigation of management practices to optimize cover crop-based weed mitigation in Canadian sweet corn production
Bibliographic record
Abstract
Fall sown cereal rye (Secale cereale L.) has gained popularity as a roller crimped cover crop due to its weed-suppressive capabilities, but management recommendations are needed to promote adoption in Canadian sweet corn production. Field trials were conducted to investigate the effect of rye cultivar, seeding rate, and roller crimping direction on weed control and sweet corn yield to determine best management practices. In the first trial, two rye cultivars (early vs. standard maturity) were compared at three seeding rates (150, 300, and 600 seeds m-2). In the second trial, rye planting directions (North-South vs. East-West) and roller crimping directions (parallel vs. perpendicular) were tested. Weed control and sweet corn yield were highest in the standard cultivar sown at 300 to 600 seeds m-2 and in parallel roller crimping for either rye planting direction; however, supplemental weed control measures should be investigated to reduce yield loss from uncontrolled weeds.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".