Toxic and Environmental Effects of Neonicotinoid Based Insecticides
Bibliographic record
Abstract
The insecticide known as neonicotinoid has negative impacts on the ecosystem, human health, and the environment; specifically, its effects on the relationship between crop yields and the death rate of natural pollinators, such as bees, affect food security. The active ingredients in neonicotinoids include imidacloprid, clothianidin, thiamethoxam, acetamiprid, sulfoxaflor, and thiacloprid, which are sold under various trade names. For many of the components of these toxic insecticides, patents have been expired; however, farmers and consumers who continue to use these chemicals are unaware of the products’ toxicity and the environmental effects they have. Thus, agricultural industries are required to consider diverse methods to minimize neonicotinoid use in farming operations and move away from the current prevailing methods. In this short review, the negative effects of neonicotinoid use; the toxic components, health effects, and environmental regulations of neonicotinoids; and sustainable methods to minimize their use are examined.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".