Different Heavy Metal Concentrations in Plants and Soil Irrigated with Industrial / Sewage Waste Water
Bibliographic record
Abstract
Application of waste water for irrigation purposes has increased over the past years. This waste water contains high amount of trace elements and heavy metals. Objectives of this study were to evaluate the concentration of iron (Fe), lead (Pb) and manganese (Mn) in soil irrigated with waste water at different depths and also in the leaves and flowers of vegetables grown in that soil. Samples were collected from vegetable farms located along drain where vegetables were grown by untreated sewage water. Plant samples were washed and cut into pieces, air dried in fluidized bed dryer. After digestion, concentration of heavy metals was detected by atomic absorption spectrophotometer (AAS). The results revealed that heavy metals concentration in soil irrigated with waste water was higher the toxicity level at depth of 0-15cm than the lower layer 16-30cm while the leaves and fruits of vegetables also showed higher concentration of heavy metals. The maximum concentration of lead, iron and manganese was recorded in soil samples taken from Nawabanwala, Malkanwala and Sheikhanwala respectively.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 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 teacher head, 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".