Characteristics and disposal options of sludge from a steel mill wastewater treatment plant
Bibliographic record
Abstract
In the present study, sludge from a steel wastewater treatment plant (SWWTP) was analyzed regarding its physicochemical characteristics and metal contents, and disposal options. For these purposes, grab sampling was used to collect 18 slurry and 18 cake sludge samples in 6 mouth (May-October 2012). Mann-Whitney U test, one sample T-test and Wilcoxon signed rank test were applied to analyze the obtained data. Canadian Soil Quality Guidelines (CSQG) and Florida Department of Environmental Protection Soil Cleanup Target Levels (FDEPSCTLs) were used to discuss the disposal fate of the generated sludge. The results showed that the order of the studied metals in the sludge was as: Fe>Al>Ca>Mg>Zn>Na>Pb>Mn>Cu>Cr>Ni>Co>Cd. It was found that due to higher concentration of Cu, Pb, Zn and Fe in the generated sludge, compared with CSQG and FDEPSCTLs, it is not suitable for residential and non-residential applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".