concentration of Cadmium in Cigarette Brands, and tobacco leaves, also in the blood sample of smokers
Bibliographic record
Abstract
A Abstract Aim : This study aimed to determine the cadmium (Cd) concentration in three different types of tobacco leaves, in the blood of the cigarette smokers, and some different imported cigarette brands and/or produced in Iran. Methods : Male volunteers, aged 40-65 year, whose blood samples were collected and classified into four groups of cigarette smokers (N=40), based on the number of cigarettes per day. Serum concentrations of heavy metal were determined using graphite furnace atomic absorption (GFAA). Also, graphite furnace atomic absorption spectroscopy technique was used for determination of all of the samples studied in this project. Results: Mean concentrations of Cd in imported cigarettes brands and produced cigarettes in Iran were 1.89±o.12 µg/g (dry weight) and 1.44±0.8 µg/g (dry weight), respectively. Average levels of Cd in smoker’s blood with 10, 20, 30, and 40 cigarettes per day were 1.31±0.14, 2.42±0.17, 3.18±0.21, and 4.38±0.18 µg per liter, respectively. The mean concentrations of Cd in Hakan, Kasham and Borazjan tobacco were 2.18 ± 0.12, 2.43±0.9, and 2.89±017µ/g (dry weight), respectively. Conclusion : Our presented data in the study showed no significant differences between different cigarette brands produced in Iran, while Rothman cigarette brand had the highest Cd concentrations among the imported cigarettes. The blood Cd concentration in smokers is dependent on the number of cigarette smoked per day. and was about four times higher than non-smokers.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".