A birds-eye-view on CRISPR-Cas system in agriculture
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
Abstract Targeted genome editing by Clustered Regularly Interspaced Short Palindromic Repeat- CRISPR-associated (CRISPR-Cas) system has revolutionized basic and translational plant research. There is widespread use of CRISPR-Cas technology which has the potential to address challenges like food insecurity and climate crisis. Crops with improved traits (e.g., higher yield, drought tolerant) that would take several years to generate can now be developed at a much reduced time, drastically expediting the availability of the crops for release in the market. However, several factors are involved in successfully applying the CRISPR-Cas system in agriculture and the widespread adoption and acceptability of genome-edited products that involve multiple institutions and people from different spheres of society. Besides the scientific and legal intricacies of releasing CRISPR-edited crops, “public perception” equally matters in successfully deploying the technology and its products. “Lack of” or “overwhelming” information can both affect the success of the CRISPR-Cas system in translational agriculture research. A bird’s-eye-view of the CRISPR-Cas genome editing tool for people from different strata of society is essential for the wide acceptability of genome-edited crops. This review provides a general overview of the CRISPR-Cas system, the concept of technology development, challenges, and regulations involved in translational research. Graphical abstract
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