Geochemical evaluation of contaminants around waste disposal site - Jawahar Nagar, Hyderabad, India
Bibliographic record
Abstract
As environmental degradation continues due to population explosion, industrialization, urbanization etc, it becomes important to understand the dynamic interaction between man and environment. The environmental geochemistry becomes a successful tool to understand the complex geochemical phenomena found particularly in the urban and sub-urban environment such as distribution, dispersion, mobility and movement of potentially toxic elements in the environment. Environmental geochemical studies were carried out around Jawahar Nagar Municipal Waste Dump Yard, Hyderabad, India, which receives over 3000 tones of solid waste round the clock from the city with population more than 6 million. The soil samples were collected and analysed using X-ray fluorescence to ascertain the extent of pollution due to potentially harmful elements in the study area. The analytical results revealed the elevated concentration of toxic/heavy metals such as Arsenic (7.50 26.5 mg.kg), Zinc (40.0 534.4 mg.kg), Chromium (35.2 158.6 mg.kg), Copper (44.8 65.4 mg.kg), Nickel (30.4 63.3 mg.kg), Vanadium (36.6 228 mg.kg) and Lead (60.5 87.5 mg.kg), which are exceeding the values prescribed by WHO Guidelines and Canadian Soil Quality Guidelines for the Protection of Environmental and Human Health. These elements have a prolonged resident time in the soil and are bio-accumulatory in nature, which pose a significant impact on environment at global scale. Based on above geochemical evaluation of pollution risks associated with metals, suitable remedial measures can be adopted to bring down the levels of metal pollution in urban environment. Electrical resistivity of Ti-rich phologopite under mantle pressures G. PARTHASARATHY AND T.A.K. REDDY National Geophysical Research Institute, Hyderabad, 500007, India (gpsarathy@ngri.res.in) Geological Survey of India, Hyderabad.-5000029
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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 | 0.001 |
| 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".