Biosafety risk assessment approaches for insect-resistant genetically modified crops
Bibliographic record
Abstract
Background: Environmental risk assessment (ERA) is imperative for commercial release of insect resistant, genetically modified crops (IR-GMCs).An insect specific, spider venom peptideω-HXTX-Hv1a (Hvt) was successfully expressed in cotton plants. The cotton plants producing Hvt protein have demonstrated resistance against economically important insect pest species. The study was performed to assess the effects of Hvt producing cotton plants on Honey bees (Apis mellifera). Methods: Three approaches were used to evaluate the effects of Hvt protein on adults of honeybees; whole plant assays in flight cages, in vitro assays with pollen of Hvt-cotton, and assays with elevated levels of purified Hvt protein. Pollens of Bt cotton or purified Bt proteins were used as control. Results: The field experiments did not yield any meaningful data due to high rate of mortality in all treatments including the control. However, the laboratory experiments provided conclusive results in which Hvt, purified or in pollens, did not affect the survival or longevity of the bees compared to the control. During the course of study we were able to compare the quality, effectiveness and economics of different experiments. Conclusions: We conclude that Hvt either purified or produced in cotton plants do not affect the survival or longevity of honey bees. We are also of the view that starting at laboratory level assays not only gives meaningful data but also saves a lot of time and money that can be spent on other important questions regarding safety of a particular transgenic crop. Hence, a purpose-based, tiered approach could be the best choice for pre-release ERA of IR-GMCs.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".