Genetic engineering for increasing fungal and bacterial disease resistance in crop plants
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
We review the current and future potential of genetic engineering strategies used to make fungal and bacterial pathogen-resistant GM crops, illustrating different examples of the technologies and the potential benefits and short-falls of the strategies. There are well- established procedures for the production of transgenic plants with resistance towards these pathogens and considerable progress has been made using a range of new methodologies. There are no current commercially available transgenic plant species with increased resistance towards fungal and bacterial pathogens; only plants with increased resistance towards viruses are available. With an improved understanding of plant signaling pathways in response to a range of other pathogens, such as fungi, additional candidate genes for achieving resistance are being investigated. The potential for engineering plants for resistance against individual devastating diseases or for plants with resistance towards multiple pathogens is discussed in detail.
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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) | 0.000 | 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