Determination of geochemical baseline and pollution of soil heavy metals in Suzhou, China
Bibliographic record
Abstract
To investigate the enrichment of soil heavy metals, 50 soil samples were collected and the vanadium (V), chromium (Cr), zinc (Zn), lead (Pb), copper (Cu) and arsenic (As) contents were measured by using an X-ray fluorescence spectrometer. The environmental geochemical baseline values of heavy metals were determined by using standardised methods, and the pollution and enrichment degrees of heavy metals were evaluated based on the geoaccumulation index method and enrichment factor method. The results show that the vanadium, chromium, copper, zinc, lead and arsenic contents vary widely, with mean values of 81.32, 65.54, 17.16, 49.28, 20.04 and 11.68 mg/kg, respectively. Except for arsenic, the average values of the other five elements are lower than the soil background values of Anhui Province. The results of the standard reference method indicate that the six heavy metal elements have a strong correlation with iron (Fe), and the baseline values of heavy metals are 81.33, 65.56, 17.18, 49.29, 20.04 and 11.67 mg/kg, respectively. The mean values of Igeofor the six heavy metals are less than 0, indicating that there is no pollution of heavy metals in the soil of Suzhou. The average enrichment factor is greater than 1, with slight enrichment, and the interference of human activities on soil heavy metals is not obvious.
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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 | 0.002 | 0.002 |
| 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".