Research on comprehensive high-yielding cultivation techniques for mulched broad beans in dryland farming areas
Bibliographic record
Abstract
Under the agro ecological circumstances in dryland farming areas in middle Gansu Province,the design method combining the routine with the binary regression was used to research into the relationship among and interrelated effect on high yield of mulched broad bean and varieties, density and the applied volume ratio among N,P and K.Meanwhile, production demonotration verifying the experiment achievements was available. On the basis of demonstration achievements, relevant analysis program was selected to simulate on computer. As a result, 23 sets of technology plan were found, through which the yield was over 4 500 kg/hm 2 and the net income was over 1 500 yuan/hm 2 , the 95% relibility range of the plan was that Canada 321 was celected as an improved variety; 210 000 seedlings/hm 2 were kept;High quality manure application volume was 60 000 kg/hm 2 ;Pure N 49.3 kg/hm 2 ~70.7 kg/hm 2 ;P 2 O 5 155.7 kg/hm 2 ~200.7 kg/hm 2 ;K 2 O65.7 kg/hm 2 ~86.8 kg/hm 2 ; The centre integ ration of the fertilizer was that high quality manure application volume was 60 000 kg/hm 2 ;Pure N 60 kg/hm 2 ;P 2 O 5 178.2 kg/hm 2 ;K 2 O 76.3 kg/hm 2 ; The ratio of N,P 2 O 5 and K 2 O was 1∶ 2.97 ∶ 1.27.
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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 | 0.000 |
| 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".