Effects of Nitrogen on Agronomic Characteristics and Yield of Soybeans From Different Regions
Bibliographic record
Abstract
Twelve soybean cultivars from different regions were used to study the effect of nitrogen fertilizer on agronomic characteristics and yield in field conditions.The results were as follows: The plant height,branches and the pods per plant of soybean cultivar improved in the treatment of nitrogen.The nodes of main stem for three groups soybean cultivars rised in the treatment of 100 kg/hm2 nitrogen fertilizer.The height of the lowest pod of current Ohio cultivar and current Ohio cultivar reduced in the treatment of 100 kg/hm2 nitrogen fertilizer.The ratio of seeds to stem for current Ohio cultivar and current Ohio cultivar improved in the treatment of nitrogen fertilizer.The yield increased by 10.61% and 1.63% for current Ohio cultivar and old Liaoning cultivar in the treatment of 200 kg/hm2 nitrogen fertilizer respectively.The yield increased by 10.47% for current Liaoning cultivar in the treatment of 100 kg/hm2 nitrogen fertilizer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".