Comprehensive Analysis on Main Characters of New Wheat Strains under Different Density
Bibliographic record
Abstract
The main characters of four new wheat strains were analyzed by cluster analysis and TOPSIS under four different planting densities in order to apply new wheat strains in agricultural production.Results of the TOPSIS showed that the 223 strains were the best,and the 2138 strains were the worst.Cluster results showed that the two strains could be divided into three categories according to different aspect:the first category was 2138 strains under two different densities and the control varieties,and the second type was 223 strains under four different densities,the third category was 2138 strains under two different densities.Combining two analytical methods in evaluating new wheat strains and four different densities showed that the comprehensive evaluated outcome was consistent by the two analysis methods,and the two methods all had advantages and disadvantages in evaluating new strains and its' suitable density.
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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) | 0.001 | 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 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".