Polarography Can Successfully Quantify Heavy Metals in Dentistry
Bibliographic record
Abstract
Background and Objectives: Due to the nutritional and behavioral patterns of children, their teeth can be a good indicator of heavy metal uptake from over the years. To determine the amount of Zn, Cu, Cd, and Pb accumulated in the body, primary teeth of children in Zanjan, Iran, were examined with a polarography device. Materials and Methods: Samples were collected from dentistry clinics of Zanjan, Iran, and were prepared for acid digestion, and then were analyzed by a polarography device for determining the concentration of lead, copper, zinc, and cadmium. Results: Data were analyzed by a t-independent test to compare different groups (p < 0.05). Based on the results obtained from this study, the mean concentrations of zinc, lead, copper, and cadmium were 245, 7.66, 5.33, and 0.0879 µg/g, respectively, which shows that the amount of each of the four elements was more than the amounts that have been reported for different countries. The results showed no significant difference between age, tooth type, and jaw groups. Conclusions: We conclude that primary teeth are an important biological indicator to evaluate the concentration of heavy elements in the human body. The high concentrations of these elements in the primary teeth analyzed in this study could be attributed to the high concentrations of these elements in the environment of Zanjan.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.006 | 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 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".