<i>Agrobacterium</i>‐mediated transformation of cereals: a promising approach crossing barriers
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
Cereal crops have been the primary targets for improvement by genetic transformation because of their worldwide importance for human consumption. For a long time, many of these important cereals were difficult to genetically engineer, mainly as a result of their inherent limitations associated with the resistance to Agrobacterium infection and their recalcitrance to in vitro regeneration. The delivery of foreign genes to rice plants via Agrobacterium tumefaciens has now become a routine technique. However, there are still serious handicaps with Agrobacterium-mediated transformation of other major cereals. In this paper, we review the pioneering efforts, existing problems and future prospects of Agrobacterium-mediated genetic transformation of major cereal crops, such as rice, maize, wheat, barley, sorghum and sugarcane.
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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 | 0.002 | 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 it