Non-carcinogenic risk assessment to human health due to intake of fluoride in the groundwater in rural areas of Gonabad and Bajestan, Iran: A case study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this study, a field research regarding groundwater contamination with fluoride and its related health risks to human health was carried out in 39 rural areas of Gonabad and Bajestan, Iran, in 2017. The results indicated that fluoride levels in two rural areas exceeded the WHO guideline. A total of 55% and 4.7% of the studied rural areas in Gonabad and Bajestan, respectively, had fluoride levels below the minimum recommended value of WHO for fluoride (0.5 mg/L). In this article, chronic non-cancer risks to three different groups of people, adults, children, and infants, for exposure to the fluoride were assessed. Health risk index values for fluoride contamination for 44% and 90% of children and infants in rural areas of Gonabad and Bajestan, respectively, were more than unity (>1), which clearly reveals that these age groups at the studied areas are at the chronic health risk due to the intake of fluoride-containing water. The order of fluoride contribution to non-carcinogenic health risk among the studied age groups was infants > children > adults. Therefore, from a public health viewpoint, it would be prudent and important that risk reduction measures be implemented to diminish the total body burden of fluoride in residents.
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.
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 | 0.003 | 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) | 0.000 | 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 it