Effects of sea louse chemotherapeutants on early life stages of the spot prawn ( <i>Pandalus platyceros</i> )
Bibliographic record
Abstract
Salmon aquaculture is among the fastest growing food-producing industries worldwide, growing from 12,000 tonnes in 1980 to over 3.2 million tonnes by 2018 (Asche et al., 2013;; FAO, 2020).Canada is now the fourth largest producer of farmed salmon behind Norway, Scotland and Chile producing over 100,000 tonnes of farmed salmon in 2019 (DFO, 2018a).This industry relies on permeable open net pen structures placed directly into nearshore coastal waters to hold the salmon (Asche et al., 2013).These open net pens are efficient for rearing salmon as the open transfer of seawater provides exposure to natural fluctuations in water conditions such as salinity, temperature, nutrients and dissolved oxygen.Outbreaks of parasitic sea lice (Lepeophtheirus salmonis and Caligus spp.) are a major issue in open net pen salmon farming worldwide (Costello, 2006;Krkoek et al., 2005).These ectoparasites feed on the host's skin, mucus and underlying tissue, leaving the host fish susceptible to secondary infection and disease (Costello, 2006).Outbreaks of sea lice represent the greatest source of mortality and economic losses to fish farms, causing estimated global losses of $500 million annually, accounting for 6% of product value (Costello, 2009;
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".