Data Review on the Variation in Sensitivity to Aquaculture Chemotherapeutants in Some Crustacean Life Stages
Bibliographic record
Abstract
Aquaculture chemotherapeutants used to control sea lice in finfish aquaculture can disperse into the marine habitat and have the potential to affect non-target species like crustaceans. Some of the compounds used (especially in Canada) include in-feed drugs such as emamectin benzoate (EMB), and ivermectin (IVER), as well as bath pesticides such as azamethiphos (AZA) and hydrogen peroxide (HP). Despite the paucity of data, crustacean life cycle stages appear to have varying sensitivities to these compounds. This data review sets out to examine the intraspecies variation in sensitivity within life stages for lobster (Homarus) and prawn (Pandalus) species. Despite limited information, it appears that prawn eggs, adults, and juveniles are less sensitive to AZA and EMB compared with larvae, whereas for lobster the opposite is true: adults and juveniles are more sensitive than larvae to AZA (there was insufficient data to assess EMB). For HP, the sensitivity of prawn eggs appears comparable to larvae, but hatching success data suggest that this important stage of development is less impacted than eggs themselves as indicated by one study. These differences are important considerations for toxicity threshold determination processes and risk assessments, which ideally are environmentally relevant, and highlight the need for more data.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".