Detection of emamectin benzoate tolerance emergence in different life stages of sea lice, lepeophtheirus salmonis, on farmed Atlantic salmon, Salmo salar L
Bibliographic record
Abstract
Emamectin benzoate has been used to treat sea lice, Lepeophtheirus salmonis, infestations on farmed Atlantic salmon, Salmo salar. Recent evidence suggests a reduction in effectiveness in some locations. A major challenge in the detection of tolerance emergence can be the typically low proportion of resistant individuals in a population during the early phases. The objectives of this study were to develop a method for determining differences in temporal development of tolerance between sea lice life stages and to explore how these differences might be used to improve the monitoring of treatment effectiveness in a clinical setting. This study examined two data sets based on records of sea lice abundance following emamectin benzoate treatments from the west coast of Scotland (2002–2006) and from New Brunswick, Canada (2004– 2008). Life stages were categorized into two groups (adult females and the remaining mobile stages) to examine the trends in mean abundance and treatment effectiveness. Differences in emamectin benzoate effectiveness were found between the two groups by year and location, suggesting that an important part of monitoring drug resistance development in aquatic ectoparasites may be the need to focus on key life stages.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".