Optimization and field use of a bioassay to monitor sea lice Lepeophtheirus salmonis sensitivity to emamectin benzoate
Bibliographic record
Abstract
A bioassay for sea lice Lepeophtheirus salmonis sensitivity towards emamectin benzoate (EMB) was validated for field use. A probit regression model with natural responsiveness was used for the number of affected (moribund or dead) sea lice in bioassays involving different concentrations of EMB. Bioassay optimization included an evaluation of the inter-rater reliability of sea lice responsiveness to EMB and an evaluation of gender-related differences in susceptibility. Adoption of a set of bioassay response criteria improved the concordance (evaluated using the concordance correlation coefficient) between raters' assessments and the model estimation of EC50 values (the 'effective concentration' leading to a response of 50% of the lice not prone to natural response). An evaluation of gender-related differences in EMB susceptibility indicated that preadult stage female sea lice exhibited a significantly larger sensitivity towards EMB in 12 of 19 bioassays compared to preadult males. In order to evaluate sea lice sensitivity to EMB in eastern Canada, the intensive salmon farming area in the Bay of Fundy in southwestern New Brunswick was divided into 4 distinct regions based on industry health management practices and hydrographics. A total of 38 bioassays were completed from 2002 to 2005 using populations of preadult stage sea lice collected from Atlantic salmon Salmo salar farms within the 4 described regions. There was no significant overall effect of region or year on EC50 values; however, analysis of variance indicated a significant effect of time of year on EC50 values in 2002 and a potential effect in 2004 to 2005. Although the range of EC50 values obtained in this 3 yr study did not appear sufficient to affect current clinical success in the control of sea lice, the results suggest a seasonal- or temperature-associated variation in sensitivity to EMB. This will need to be considered if changes in EMB efficacy occur in the future.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".