Genetically modified soybean expressing insecticidal protein (Cry1Ac): Management risk and perspectives
Bibliographic record
Abstract
A Bt soybean has been recently developed, thus, efficiently regulating the populations of major lepidopteran pests. However, in other cases, these benefits have been reduced or lost because of the rapid evolution of pest resistance to the Bt toxins in transgenic crops. When pest populations are exposed to Bt crops and to refuges (non- Bt plants), the evolution of resistance is governed by the fitness of resistant individuals relative to susceptible individuals for both the presence and absence of Bt toxins. One major ecological concern regarding the biosafety of Bt crops on the environment is their potential effects on non-target organisms, especially predators and parasitoids that play an important role in pest control. This information is important for supporting insect resistance management (IRM) programs and for improving agricultural practices in a crop production system with Bt plants. Before the use of Bt plants for insect pest control in Brazil is adopted, IRM programs should be established to ensure the sustainability of this technology for integrated pest management (IPM). This review presents data on Bt soybean and lepidopteran pests as well as on the importance of natural enemies as a form of biological control, and applications for IPM and IRM.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".