Expert opinions on the regulation of plant genome editing
Bibliographic record
Abstract
Global food security is largely affected by factors such as environmental (e.g. drought, flooding), social (e.g. gender inequality), socio-economic (e.g. overpopulation, poverty) and health (e.g. diseases). In response, extensive public and private investment in agricultural research has focused on increasing yields of staple food crops and developing new traits for crop improvement. New breeding techniques pioneered by genome editing have gained substantial traction within the last decade, revolutionizing the plant breeding field. Both industry and academia have been investing and working to optimize the potentials of gene editing and to bring derived crops to market. The spectrum of cutting-edge genome editing tools along with their technical differences has led to a growing international regulatory, ethical and societal divide. This article is a summary of a multi-year survey project exploring how experts view the risks of new breeding techniques, including genome editing and their related regulatory requirements. Surveyed experts opine that emerging biotechnologies offer great promise to address social and climate challenges, yet they admit that the market growth of genome-edited crops will be limited by an ambiguous regulatory environment shaped by societal uncertainty.
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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".