Molecular Mechanism Analysis of Improving the Development of Rice Growth Organs Using Gene Editing Technology
Bibliographic record
Abstract
Rice ( Oryza sativa ) is one of the most important food crops in the world, and the development of its reproductive organs is crucial for yield and food safety. With the rapid development of gene editing technology, researchers have begun to explore the use of gene editing to improve the development of rice reproductive organs, in order to improve yield and quality. This review aims to explore how gene editing technology can reveal the molecular mechanisms of rice reproductive organ development and explore its potential applications to promote sustainable agriculture and food safety. This study explores the importance of rice as a pillar crop of global food security, as well as the key impact of reproductive organ development on its yield and quality. Then, we introduced the basic principles of gene editing technology, including the working principle of CRISPR-Cas9 technology and the design of RNA guided sequences. Next, we delved into the molecular mechanisms of rice reproductive organs, including the development of roots, leaves, and panicles, and their importance in nutrient absorption, photosynthesis, and seed yield.
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 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 | 0.000 | 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".