Mapping of three QTLs that regulate internode elongation in deepwater rice
Bibliographic record
Abstract
The internodes of deepwater rice can elongate in response to rises in water level. This unique character allows deepwater rice to survive severe flooding during the monsoon season in South and Southeast Asia. Our previous quantitative trait locus (QTL) analysis of a deepwater rice cultivar (Oryza sativa) detected QTLs on chromosomes 1, 3 and 12. In this study, we produced three nearly isogenic lines (NILs) possessing each of the three QTLs by backcross introduction of each chromosomal region into a non-deepwater rice cultivar. The NILs showed internode elongation under deepwater conditions, and we were able to demonstrate the existence of the QTLs and to evaluate the effect of each QTL. Using progenies of the NILs, we mapped all QTLs between molecular markers. Comparison of the location of the most effective QTL between the rice cultivar (O. sativa) and a wild rice species (O. rufipogon) indicated that the QTL on chromosome 12 is common and is the most important QTL for internode elongation in deepwater condition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".