Dental amalgam and urinary mercury concentrations: a descriptive study
Bibliographic record
Abstract
BACKGROUND: Dental amalgam is a source of elemental and inorganic mercury. The safety of dental amalgam in individuals remains a controversial issue. Urinary mercury concentrations are used to assess chronic exposure to elemental mercury. At present, there are no indications of mercury-associated adverse effects at levels below 5 μg Hg/g creatinine (Cr) or 7 μg Hg/L (urine). The purpose of the present study is to determine the overall urinary mercury level in the Canadian general population in relation to the number of dental amalgam surfaces. METHODS: Data come from the 2007/09 Canadian Health Measures Survey, which measured urinary mercury concentrations in a nationally representative sample of 5,418 Canadians aged 6-79 years. Urinary mercury concentrations were stratified by sex, age, and number of dental amalgam surfaces. RESULTS: The overall mean urinary mercury concentration varied between 0.12 μg Hg/L and 0.31 μg Hg/L or 0.13 μg Hg/g Cr and 0.40 μg Hg/g Cr. In general, females showed slightly higher mean urinary mercury levels than men. The overall 95th percentile was 2.95 μg Hg/L, the 99th percentile was 7.34E μg Hg/L, and the 99.9th percentile was 17.45 μg Hg/L. Expressed as μg Hg/g Cr, the overall 95th percentile was 2.57 μg Hg/g Cr, the 99th percentile was 5.65 μg Hg/g Cr, and the 99.9th percentiles was 12.14 μg Hg/g Cr. Overall, 98.2% of participants had urinary mercury levels below 7 μg Hg/L and 97.7% had urinary mercury levels below 5 μg Hg/g Cr. All data are estimates for the Canadian population. The estimates followed by the letter "E" should be interpreted with caution due to high sampling variability (coefficient of variation 16.6%-33.3%). CONCLUSIONS: The mean urinary mercury concentrations in the general Canadian population are significantly lower than the values considered to pose any risks for health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
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".