Analysis of Heavy Metal in Electrocoagulated Metal Hydroxide Sludge (EMHS) from the Textile Industry by Energy Dispersive X-Ray Fluorescence (EDXRF)
Bibliographic record
Abstract
Environmental pollution due to discharges of heavy metal containing sludge from textile industries is a common nuisance in Bangladesh, where no treatment of sludge is carried out before final disposals. Energy Dispersive X-ray Fluorescence (EDXRF) was employed in the present study to analyze the heavy metal content of Electrocoagulated Metal Hydroxide Sludge (EMHS) collected from a composite textile industry. Thirteen heavy metals, viz., Mn, Ti, Cu, Zn, Ni, Sr, V, Cr, Zr, Hg, Cd, Nb and Ga, were detected. Mn, Ni, Cu, Zn and Cd exceeded the permissible limit to apply the EMHS in agricultural land. Cr, Ni, Cu and Zn were compared to the values of the European legislation to evaluate the environmental risk and to classify the wastes as inert wastes or as wastes that have to be control landfilled. EMHS was categorized as class I and needs to be deposited in controlled landfills.
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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 | 0.000 |
| 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 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".