Risk assessment of potentially toxic elements in soil surrounding the Golesh ferronickel mine, Kosovo
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Bibliographic record
Abstract
Purpose. The objective of this study was to assess the risk of potentially toxic elements in soil samples surrounding ferronickel mines in the Golesh massif, Republic of Kosovo. Methods. In total, 14 potentially toxic elements (Al, As, Cd, Co, Cr, Cu, Fe, Li, Mg, Mn, Ni, Pb, V and Zn) were investigated. Basic statistics, Pearson correlation, Principal Component Analysis (PCA), and Pollution indices (CF, PLI, Igeo, and EF) were used to explain better the data on metal concentrations in the soil samples. Findings. Five groups of elements were identified by PCA, based on their geogenic or anthropogenic origin. The contamination factor for nickel ranged from 6.9 to 166, with a mean value of 65.17. Cobalt and magnesium also had high mean values of contamination factor: 10.38 and 9.76, respectively. The PLIsite for 14 locations were highly polluted with metals (PLI > 4), and the PLIzone of the whole territory investigated was 3.5. The mean value of Igeo for nickel was 5.44, for cobalt (2.79) and for magnesium (2.7). The mean value of enrichment factor (EF) for nickel, cobalt and magnesium was 233.7, 35.26 and 19.16, respectively. Originality.Soil samples were collected from 30 different locations in accordance with the soil sampling protocol. The samples were sent for further analysis at the ACME, Ltd. laboratory in Vancouver, Canada. The soil samples were digested with aqua regia, and the content of 14 chemical elements was determined using inductively coupled plasma-mass spectrometry (ICP-MS). Practical implications. Based on statistical analysis and pollution indices, we concluded that most soil samples were highly polluted with Ni, Co, and Mg, resulting from the ferronickel and magnesite mines located in the region under investigation.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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