Growth Analysis on the Process of Grain Filling in Hybrid Wheat 901 and Its Parents
Bibliographic record
Abstract
Using Matlab process, the grain filling process of hybrid wheat 901 and its parents was fitted by Richards equation on computer in order to study the characteristics of grain filling in hybrid wheat 901. The active grain growth period of hybrid wheat 901 was 6 days longer than that of Shan 229, its final grain weight (43.7 g?000-grain-1) was higher than that of Shan 229 (36.3 g?000-grain-1). N values of 901 and R205 were both less than 1, their grain growth was fast in the early filling stage, slower in the middle-late stage. N value of Shan 229 was 1, its growth was slow in the early stage and fast in the middle stage. The duration of early stage of 901 was short and the duration of middle-late stage of 901 was longer. The situation of Shan 229 was totally reversed. In parents, the father plant R205 was similar with hybrid wheat 901, its mother plant K3314A was similar with Shan 229. It was also found that Richards equation was more suitable for fitting the grain filling process of wheat than Logistic equation.
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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 | 0.000 |
| 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".