Habitat Selection by Two Species of Cleaner Fishes That May be Beneficial in Removing Sea Lice From Cultured Salmon
Bibliographic record
Abstract
Sea lice are detrimental ectoparasites that attach to Atlantic salmon causing physiological damage and costing farmers millions in inventory loss and treatments. Cleaner fishes have been introduced into sea cages to act as a biological control of sea lice which is likely a solution for Canadian salmon aquaculture industries. To improve cleaner fish foraging efficiency, this study seeks to determine the optimal habitat for cleaner fishes in Canadian aquaculture. I hypothesized that to be effective cleaner fishes, both the cunners and the lumpfish require habitats that provide them with shelter and places for rest because neither species live solely in the water column. My second hypothesis was that the cunners and the lumpfish require different habitats due to their different morphologies. Habitat comparisons were conducted with three habitats and a control in each individual fishes tank for a total of 8 cunners and 25 lumpfish. It was determined that only cunners required shelter, possibly due to the lumpfish’s ability to adhere to the glass tank walls for rest. Moreover, there was no significant difference in habitat preference between the two species. However, the lumpfish were less preferential between habitat and preferred three of the four habitats equally. It should be noted that the lumpfish and the cunners utilized the same habitats in separate ways to better fit their species-specific requirements; so future research on the co-existence of the two species could lead to increased foraging efficiency through two-species cleaner fish systems.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".