Survey of total mercury in some edible fish and shellfish species collected in Canada in 2002
Bibliographic record
Abstract
Total mercury was measured in the edible portions of 244 selected fish and shellfish purchased in Canada at the retail level. By species, average mercury concentrations ranged from 0.011 microg g(-1) for oysters to 1.82 microg g(-1) for swordfish. The predatory fish contained the highest concentrations of mercury: swordfish (mean 1.82 microg g(-1), range 0.40-3.85 microg g(-1)), marlin (1.43, 0.34-3.19 microg g(-1)), shark (1.26, 0.087-2.73 microg g(-1)), and canned, fresh and frozen tuna (0.35, 0.020-2.12 microg g(-1)). Levels of mercury in the fresh and frozen tuna contained a mean of 0.93 microg g(-1) (range 0.077-2.12 microg g(-1)) and were substantially higher than in the canned tuna (0.15, 0.02-0.59 microg g(-1)). In the canned tuna, mercury concentrations varied with subspecies, with the highest average concentrations being found in Albacore tuna (mean 0.26 microg g(-1), range 0.19-0.38 microg g(-1)) and the lowest (0.047, 0.025-0.069 microg g(-1)) in five samples for which the subspecies of tuna were not identified. Mean concentrations of mercury in swordfish and fresh and frozen tuna were up to three times higher than reported for the USA. Dietary intake estimations found that provided fresh and frozen tuna, marlin, swordfish or shark are consumed once a month or less, the dietary intakes of total mercury by women of child-bearing age, averaged over 1 month, would fall below the Joint FAO/WHO Expert Committee on Food Additives provisional tolerable weekly intake for total mercury. The current Canadian advisory to children and women of child-bearing age is to limit their consumption of fresh and frozen tuna, swordfish and shark to no more than one meal per month.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".