The Establishment of Ningxia Japonica Rice Core Collection by the Value of Genotype
Bibliographic record
Abstract
According to the 7QTL of genetic diversity,used 250 Japonica varieties of Ningxia as materials to study the establishment of Japonica core collection.By statistical analysis technique of best linear unbiased prediction(BLUP),the genotype value of the materials was predicated.The different genetic distance,sampling method and clustering method were estimated by Means,Variance,Range,Coefficient of variation and Rand Analysis Method according 2 genetic distances(Mahalanobis Distance and Euclidian distance),3 sampling method(multi-times random sampling,multi-time preferred sampling and multi-times deviation smapling),8 clustering method(shortest distance method,complete linkage,group average method,barycenter method,UPGMA,varied UPGMA,flexible method,sum of square of the deviations method).The results showed that Mahalanobis Distance was prefered to Euclidian distance,multi-times deviation smapling was prefered to random sampling preferred sampling,the best clustering were the shortest distance method and flexible method,the best sampling ratio was 15%.37 Ningxia Japonica rice core collection were established by Mahalanobis Distance,multi-times deviation smapling,15% sampling ratio and the shortest distance method.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".