Rapeseed Planting as Green Manure Improving Rice Growth and Production
Bibliographic record
Abstract
In order to understand the effects of rapeseed planting as green manure on the growth and yield of rice cultivar ‘Qing xiang ruan geng’, a rapeseed cultivar ‘Huyou21’ were used as green manure returning to field at flowering stage. The results showed that the rice plant height and chlorophyll content increased under the treatment of rapeseed returning as green fertilizer, and also increased under 20% fertilizer reduction after rapeseed returning to field. With the amount of rapeseed returning increased, the rice yield and the yield-component traits including grains per panicle and productive panicles number increased, while the 1000-grain weight deceased, but there was no statistical difference. In addition, when the rapeseed returning amount was 22.5 t/hm 2 , the rice yield was increased significantly, and also increased under that condition with 20% fertilizer reduction.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".