Duel-purpose winter canola in the Pacific Northwest : forage management
Bibliographic record
Abstract
As winter canola (Brassica napus) continues to gain acceptance as a viable broadleaf crop in the predominantly cereal rotations of the Pacific Northwest (PNW), dual-purpose winter canola is beginning to gain interest. Not only does canola provide benefits, such as improving weed control, breaking disease and pest cycles, and increasing water infiltration, but Washington State University (WSU) research has also shown increased wheat yields following a canola crop. As the name suggests, dual-purpose winter canola serves two purposes: fall forage or silage and grain harvest. Canola forage could be advantageous in the inland PNW where late summer and fall pasture is often in short supply. While grown successfully elsewhere (mainly Australia), the feasibility of dual-purpose canola in the PNW has not been thoroughly investigated. Our study investigates the effect of different fertilizer rates and timing on forage and grain yield as well as nitrate and sulfur accumulation in winter canola. The Washington State Oilseed Cropping Systems Research and Extension Project (WOCS) is funded by the Washington State Legislature to meet expanding biofuel, food, and feed demands with diversified rotations in wheat based cropping systems. The WOCS fact sheet series provides practical oilseed production information based on research findings in eastern Washington.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".