Assessment of Soil Contamination due to Heavy Metals: A Case Study of Rakhial Industrial Area
Bibliographic record
Abstract
The purpose of this study is to investigate the current status of heavy metal soil pollution in one of the cradles of industry in India, the Rakhial Industrial area in the city of Ahmedabad, Twenty-five soil samples were collected from the top 5 cm of the soil layer and were analyzed for heavy metal concentrations of Cu, Ni, Zn and Cr. The data reveal a remarkable variation in heavy metal concentration among the sampled soils; the mean concentrations of Cu, Ni, Zn and Cr were compared with the standards of different countries like Canada, Australia, Norway, Taiwan etc. for Maximum allowable limits of heavy metals in soil. Soil samples were also analyzed to determine fixed metals present in soils if any and results showed that all metals were fixed solids and do not get carried away with rain water. GIS Mapping of study area for each metal will be done to demonstrate the distribution of heavy metals concentration.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".