Assessing the Environmental and Health Adverse Effects of Mercury Released From Dental Amalgam: A Literature Review
Bibliographic record
Abstract
This paper reviews the most available data on the possible adverse effects of mercury released from amalgam that comprises of 50 % pure mercury, 35 % silver, 12-13 % tin, 2 % copper and to up1 % zinc, indium, platinum and palladium. Despite the possible health risks of mercury from amalgam on the nervous, respiratory, renal, and endocrine systems, it is however, used in some countries, even though Sweden, Denmark, Canada, the United States and Japan have long banned the use of amalgam. Amalgam restorations are one of the main mercury-releasing sources (1800-2700 tons per year) of contamination. During chewing, grinding, brushing of teeth, breaking down of amalgam and as the temperature of the oral environment increases mercury vapor will be released. The mercury vapor enters atmosphere, wastewater in dental offices, all systemic organs, especially the lower respiratory tract, can affect the renal-urinary system or enters breast milk, fetus and finally transmits to infants. The mercury level released from amalgam in blood, urine, hair and nail of large populations of dentists, dental assistants and pregnant women is higher than the safe levels. The main neurological and psychological effects of mercury vapor include in the form of sleep disorders, amnesia, mental disorders, hair loss, memory disturbances, multiple sclerosis, Parkinson's, kidney diseases, gene-toxicity, Alzheimer, Autism, skin allergies-cancer, infertility, low-birth-weight infants and heart diseases. In order to avoid further amalgam risks to the dentists, dental assistants, pregnant women and wildlife ecosystem, it is suggested to replace the dental amalgam by composite resins.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".