Global perspectives on field-evolved resistance to transgenic Bt crops: a special collection
Bibliographic record
Abstract
Crops genetically engineered to produce insect-killing proteins from Bacillus thuringiensis (Bt) have revolutionized management of some major pests, but their efficacy is reduced when pests evolve resistance. Practical resistance, which is field-evolved resistance that reduces the efficacy of Bt crops and has practical implications for pest management, has been reported in 26 cases in seven countries involving 11 pest species. This special collection includes six original papers that present a global perspective on field-evolved resistance to Bt crops. One is a synthetic review providing a comprehensive global summary of the status of the resistance or susceptibility to Bt crops of 24 pest species in 12 countries. Another evaluates the inheritance and fitness costs of resistance of Diabrotica virgifera virgifera to Gpp34/Tpp35Ab (formerly called Cry34/35Ab). Two papers describe and demonstrate advances in techniques for monitoring field-evolved resistance. One uses a modified F2 screen for resistance to Cry1Ac and Cry2Ab in Helicoverpa zea in the United States. The other uses genomics to analyze nonrecessive resistance to Cry1Ac in Helicoverpa armigera in China. Two papers provide multi-year monitoring data for resistance to Bt corn in Spain and Canada, respectively. The monitoring data from Spain evaluate responses to Cry1Ab of the corn borers Sesamia nonagrioides and Ostrinia nubilalis, whereas the data from Canada track responses of O. nubilalis to Cry1Ab, Cry1Fa, Cry1A.105, and Cry2Ab. We hope the new methods, results, and conclusions reported here will spur additional research and help to enhance the sustainability of current and future transgenic insecticidal crops.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".