Demonstration of Soybean Varieties and Seeding Date for Observation in North-Central Saskatchewan
Bibliographic record
Abstract
Producers in north-central Saskatchewan could benefit from the addition of soybeans to their crop rotations. Soybean production would help lengthen crop rotations, provide opportunities for control of grassy weeds, and reduce fertilizer inputs and disease levels. Recent field trials have suggested that soybeans could successfully be grown in the north-central region of the province. Due to local climatic conditions, soybeans often experience yield losses due to spring or fall frosts. Yield losses due to fall frosts can be reduced by earlier seeding of soybeans, though this increases the risk of spring frosts. Tillage can help warm the soil in the spring by blackening it, which could reduce the risk of cold injury to seedlings. Finally, with the development of new shorter-season soybean varieties, the risk of major yield losses is reduced. This trial aimed to demonstrate soybean varieties for producers in the north-central region, examine the effects of seeding date on yield, and explore the potential benefits of warming the soil by tillage.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".