Study on Biological Significance of Female Fertility for Kernel Number per Spike in Wheat
Bibliographic record
Abstract
To study the relationship of female fertility and kernel number per spike in wheat,two small populations with 60 varieties or lines alternatively,one called S involved(female sterile line S)diverse extreme population and another called variety diverse extreme population,were composed as tested populations,42 polymorphic SSR markers in wheat genome were selected as background marker stotest.Its ′ population genetic structure,the MLM mode lins of tware TASSEL was used to check 210 polymorphic markers association degree with phenotype female fertility(international fertility-I.F.and domestic fertility-D.F),the highly associated markers with phenotype from small population analysis were verified in relatively big variety population and S involved bigger population,find highly associated markers with kernel number per spike in wheat.Total 2(Xgwm570-6A,Xwmc776-4A)association markers were found by two small extreme populations with phenotype kernel number per spike.Total 2(Xwmc25-2B/2D,Xwmc168-7A)association markers were found by two small variety populations with phenotype kernel number per spike.It was believed that 2D and 5B loci were associatied with kernel number per spike.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".