Hair Mercury Levels of Women of Reproductive Age in Ontario, Canada: Implications to Fetal Safety and Fish Consumption
Bibliographic record
Abstract
roductive age in relation to fish intake in e Motherisk Program for information onICP-MS Inductively coupled plasma mass spectrometryC ompared with other types of meat, fish are a source of high-quality lean protein and n-3 polyunsaturated fatty acids, which are essential for growth of the developing fetal brain.1 The predominant drawback of fish consumption for ex-pectant mothers is that all fish contain traces of methyl mercury, a known developmental neurotoxin. Methyl mercury concentration varies widely among fish species. Top predatory fresh-water fish frommercury-contaminated lakes typically con-tain the highest levels.2 Although epidemics in which large numbers of people were affected by high doses of methyl mercury in Japan3 and Iraq4 affirmed the fact that consumption of high concentrations of methyl mercury in foodstuffs by pregnant women can cause severe neurodevelopment problems in offspring,5 the implications of much lower level exposures, such as those occurring in fish-eating populations today, are largely unknown. The threshold that will adversely affect the developing fetus is debated. In January 2001, the US Food and Drug Administration (FDA) and the US Environmental Protection Agency (EPA) issued advisories counselling pregnant women to avoid consuming specified long-lived predatory fish, which may contain high levels of organic mercury, and to limit ingestion of all other fish.6,7 After this advisory was issued, it has been found that many Amer-
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".