Assessment of Levels of Elements Concentrations (Pb, As, Cr) in Groundwater and its Environmental Impacts in the Yaychi Region, Kirkuk / Northern Iraq
Bibliographic record
Abstract
The present study aims to assess the pollution of groundwater with toxic heavy elements and their carcinogenic and non-carcinogenic effects on health in the study area. For this purpose, 5 samples of groundwater wells were taken and analyzed for their content of the elements (Pb, As, Cr) using the ICP-MS device in the ACME laboratory in Vancouver / Canada. The results of these five wells showed that their concentrations rates increased according to the following order Pb> Cr> As, as they reached 45.34, 11.8, and 0.74 µg l-1, respectively, and the lead, arsenic and chromium levels in the five samples were within the permitted ranges according to FAO standards, the spatial distribution of the three elements showed that the lead concentration in groundwater was high in the eastern regions, which may be due to the impact of vehicle emissions and agricultural activities, while arsenic and chromium concentrations were high in the central and southwestern regions of the study area, which may be attributed to the effects of agricultural and industrial activities. And it was found by applying the indicators of heavy elements pollution (MI, HPI) and health risk factors that the five wells under study are not contaminated to low pollution with these elements respectively, and do not pose any carcinogenic and non-carcinogenic health risks to the population of the study area of adults and children through skin contact pathway.
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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 | 0.001 |
| 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".