Silencing of Molecular Targets with Relevance to Insecticide Resistance in Colorado Potato Beetle Using dsRNA.
Bibliographic record
Abstract
Various approaches based on RNA interference (RNAi) have garnered significant attention in the field of insect pest management in recent years. For example, the use of double-stranded RNA (dsRNA) has notably been investigated to target transcripts of interest with relevance to insecticide resistance in multiple pests and has emerged as a potential tool to be deployed in agricultural fields in the near future. A careful characterization of a given dsRNA in a laboratory setting, including the assessment of dsRNA-mediated molecular and phenotypical changes observed in the targeted pest upon dsRNA exposure, is nevertheless essential prior to its use in field-based study. The current chapter thus describes the process via which a dsRNA, aimed at a molecular target underlying insecticide response in the Colorado potato beetle Leptinotarsa decemlineata, is conceived, synthesized and injected. Assessment of knockdown efficiency in injected insects is further presented.
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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 | 0.000 | 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) | 0.001 | 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".