Mercury comparisons between farmed and wild Atlantic salmon (<i>Salmo salar</i>L.) and Atlantic cod (<i>Gadus morhua</i>L.)
Bibliographic record
Abstract
Wild and farmed Atlantic salmon (Salmo salar L.) and Atlantic cod (Gadus morhua L.) were collected to assess changes in mercury with size in wild vs. farmed fish. Mercury concentrations were compared with Health Canada and United States Environmental Protection Agency consumption guidelines. Lipid dilution of mercury was examined by comparing lipid-extracted (LE) and non-lipid-extracted (NLE) flesh samples in both farmed and wild fish. Mercury concentrations in the flesh and liver of farmed salmon were significantly lower than concentrations in wild salmon of similar fork length (P<0.001), possibly due to growth dilution in rapidly growing farmed fish. Mercury concentrations were higher in LE tissue compared with NLE (P<0.05), suggesting lipid dilution of mercury in farmed fish with a high lipid content. Farmed cod, which do not grow more rapidly than wild cod, did not have significantly different flesh and liver concentrations compared with wild cod of similar fork length (P>0.05). Between species of farmed fish, cod had significantly higher mercury concentrations than salmon (P<0.05), but neither farmed nor wild salmon mercury concentrations exceeded federal consumption guidelines. These results suggest that rapid growth rates and a high lipid content may play important roles in regulating concentrations of contaminants such as mercury.
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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 | 0.001 | 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".