Conserving the efficacy of insecticides against <i>Plutella xylostella</i> (L.) (Lep., Plutellidae)
Bibliographic record
Abstract
Abstract: The diamondback moth (DBM), Plutella xylostella (L.) (Lep., Plutellidae), is one of the most destructive insect pests of crucifers worldwide. It was the first crop insect reported to be resistant to DDT and now in many crucifer‐producing regions it has shown significant resistance to almost every insecticide applied in field including biopesticides such as crystal toxins from Bacillus thuringiensis and spinosyns from Saccharopolyspora spinosa . In certain parts of the world, economical production of crucifers has become almost impossible because of its resistance to insecticides and resulting control failure. A coordinated resistance management program needs to be implemented with the involvement of pesticide industry, local pesticide regulatory authorities, scientists and farmers. The judicious use of chemicals in conjunction with other control measures (e.g. biological control agents, resistant varieties, proper fertilization rates) is the best way to manage DBM and other pests of cruciferous crops. Introduction of glucosinolate‐sulphatase inhibitors as plant‐incorporated‐products or sprayable material may also lead to a novel pest management strategy.
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) | 0.000 | 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) | 0.002 | 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".