Assessment of Carcinogenic and Non-Carcinogenic Risk Lead in Bottled Water in Different Age Groups in Bandar Abbas Ciry, Iran
Bibliographic record
Abstract
The presence of heavy metals such as lead in drinking water resources can be dangerous for human because of toxicity and biological accumulation. The consumption of water or food which contains lead in high concentration can lead to prevent from Hemoglobin Synthesis (Anemia) and Kidney diseases. In this present study, the researcher collected 432 samples of bottled water in the popular marks in summer and winter from the surface of Bandar Abbas. The lead concentration was measured by atomic absorption Spectrophotometer in model DR2800 through the Dithizone method. CDI, R and HQ which are caused by lead for adult men, women and children, have been calculated and evaluated through the equations of EPA and WHO. The mean concentration of lead, which is 3.46± 0.47 µg/l, and its range, which is 1.9-17.6 µg/l, are lower than the guideline of WHO (10 µg/l) and MPC of EPA is (15 µg/l). But the 40 samples of the bottled water (9.2%) have the concentration higher than guideline WHO and 8 samples (1.85%) has the concentration higher than the permissible limits of the EPA. CDI in different age groups is as following manner: Children>adult men>adult women. CDI in children is more than twice as much as in the adult men and women. The R of lead for children (24E-7), adult men (11E-7) and for adult women (10E-7) are more than the acceptable level of R in EPA (1E-6) but less than the acceptable level of R in WHO (1E-4). Since HQ of adult men (34E-5), adult women (31E-5) and children (84E-5), is lower than 1, it can be said that the population of Bandar Abbas is in a safe area regarding the HQ of the bottled water's lead.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".