Analysis and management of resistance to chemotherapeutants in salmon lice, <i>Lepeophtheirus salmonis</i> (Copepoda: Caligidae)
Bibliographic record
Abstract
In Northern Europe and Canada, the salmon louse, Lepeophtheirus salmonis (Krøyer), seriously affects the marine phase of salmon production. Although the problem is long-standing, the development of sustainable methods of pest management has been unable to keep pace with the intensification of production, leading to large-scale reliance on very few chemotherapeutants. This runs the risk of selecting for genetically determined resistance in target organisms. There are many examples of similar evolutionary adaptations in arthropod pests of arable crops, livestock and human health. Several hundred pest species are now documented as being resistant to one or more chemical classes of insecticides and acaricides. Many of these compounds are identical or closely related to ones currently employed against salmon lice. It is, therefore, opportune to consider what lessons have been learnt from contending with resistance in terrestrial organisms, the implications for sustainable use of chemotherapeutants in aquaculture, and the potential for developing effective resistance management strategies. An EU-funded project named SEARCH (QLK2-CT-2000-00809) has been initiated to explore in more detail the diagnosis, incidence, dynamics and management of resistance to chemotherapeutants in L salmonis.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".