Intercropping of Corn with Soybean and Lupin for Silage: Effect of Seeding Date on Yield and Quality
Bibliographic record
Abstract
Abstract Intercropping of corn with legumes is an alternative to corn monocropping and has a number of advantages, for example, lower levels of inputs, lower costs of production and better silage quality than the monocrop system. An experiment was carried out at two sites in 1993 and 1994 to investigate the effects of seeding date (simultaneous with corn or 3 weeks later) and number of rows of large‐seeded legumes (one or two) seeded between the corn rows. The intercrop plots received 90 kg ha−1 less nitrogen fertilizer than the monocrop plots, which received 180 kg ha−1. Silage yields were sometimes decreased by the simultaneous seeding of corn and large‐seeded legumes. Protein content and concentration were not affected by most treatments and provided reasonable quality silage, despite a reduction in the amount of nitrogen fertilizer used.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".