Vertical Distribution and Mobility of Heavy Metals in Agricultural Soils along Jishui River Affected by Mining in Jiangxi Province, China
Bibliographic record
Abstract
The vertical distribution of Cd, Cr, Cu, Pb, and Zn and their mobility (except Cr) were investigated in ten agricultural soil cores, collected near non‐ferrous metal mines and smelters along Jishui River, in Jiangxi Province, China. The surface soils near mines and smelters were contaminated by Cd, Cu, Pb, and Zn, with concentrations higher than the guideline values of China. For most polluted sites, heavy metals were mainly retained in the surface soil (0–20 cm), and the contents of them became constant in deeper soil. In all soil cores, the mean content of Cr was lower than the guideline value of China. Correlation results between studied heavy metals and soil properties showed that heavy metal contents throughout the soil profile was mostly influenced by organic matter (OM), pH, and clay content. Particularly soil OM can significantly impact on transport of soil heavy metals. There were positive correlations of OM content with all studied heavy metals, and the correlations with Cr, Cu, Pb, and Zn were significant or very significant. Heavy metal mobility in the studied region were assessed using a mobility index (MI) and mobility order was Cd ≫ Pb > Cu ≈ Zn.
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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 | 0.000 | 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 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".