Méthylmercure et mercure inorganique dans les fruits de mer en conserve : 1er avril 2015 au 31 mars 2016
Bibliographic record
Abstract
Mercury is a naturally occurring metal that can be present in the environment through natural sources such as volcanoes, soils, undersea vents, and mercury-rich geological zones. It can also be released through human activities like combustion and industrial processes (such as coal-fired power generation, mining, smelting, and waste incineration). The use of mercury in batteries, fluorescent tube lighting, thermometers, and other manufactured items is also a source of mercury release into the environment. Mercury is considered a global contaminant due to its toxicity, its ability to persist in the environment, and its ability to be transported long distances within the atmosphere. Exposure to methylmercury can cause harmful effects on the digestive, immune, and nervous systems, particularly in children and foetuses, whereas inorganic mercury is corrosive to skin and eyes, and toxic to kidneys. This targeted survey generated baseline surveillance data on the levels of methylmercury and inorganic mercury in domestic and imported canned seafood products on the Canadian retail market. The CFIA sampled and analyzed 300 products, including 207 fish samples, 62 mollusk samples and 31 crustacean samples. Methylmercury was detected in 38% of samples and inorganic mercury was detected in 23% of samples tested. The levels of methylmercury and inorganic mercury in this targeted survey were comparable to those previously found in CFIA surveys and reported in literature. Only 2 samples of the 50 canned albacore tuna samples analyzed in this survey contained methylmercury concentrations (0.74 and 0.67 ppm) that were above Health Canada’s ML for total mercury in retail fish of 0.5 ppm. There are no regulations in Canada for mercury or methylmercury in the other products tested. Health Canada determined that none of the samples analyzed for metals in this survey posed a concern to human health.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".