Development of CRISPR-Cas9 Multiple Editing System for Genetic Improvement of Rice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The CRISPR-Cas9 multiple editing system has become an important tool in the field of rice genetic improvement. This review aims to outline the principles and applications of the system, emphasizing its cutting-edge position in rice breeding. The advantage of a multiple editing system is that it can simultaneously edit multiple loci to achieve precise improvement of rice yield, resistance, and quality traits. This review also discusses in detail the working principle, development process, and widespread application of multiple editing systems, briefly introduces CRISPR-Cas9 technology, explains how multiple editing systems can achieve efficient multi gene editing, and delves into the specific applications of multiple editing systems in rice genetic improvement, including increasing yield, increasing resistance, and improving quality. These applications have enriched the genetic resources of rice and provided new avenues for food security and sustainable agricultural development.
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.
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 | 0.000 |
| 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) | 0.000 | 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 it