Identification of QTL for ratooning ability and grain yield traits in ratoon rice based on SSR marker
Bibliographic record
Abstract
An F_(2) population and its corresponding SSR marker linkage map were established and constructed from a cross between two indica rice cultivars, Minghui86 and Jiafuzhan. QTL for ratooning ability and grain yield traits in ratoon rice was identified and analyzed. The results showed that 1 QTL for ratooning ability (panicle per plant), 1 QTL for grain yield and 2 QTL for spikelet per panicle and seed-setting were detected. Their additive effects were from Minghui 86 with same direction effects and increasing effects. QTL conferring ratooning ability (panicle per plant), seed-setting and grain yield of ratoon rice were located in same linked regions of chromosome 7. This explained very well that the very significantly positive correlationship exists between ratooning ability and grain yield or seed-setting.
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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) | 0.002 | 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".