Extraction of metals from a contaminated sandy soil using citric acid
Bibliographic record
Abstract
Abstract Twenty‐four‐hour washing of a contaminated soil with 0.5 M citric acid reduced the levels of Cd, Cu, Zn, and Pb from 0.01, 0.04, 0.42, and 41.52 mg g‐1 to 0, 0.02, 0.18 and 5.21 mg g‐1, respectively. Extending the washing period beyond 24 hours did not influence the results significantly. Metal ions present in higher amounts were removed more easily. A column study was also conducted to compare metal leaching with surface and subsurface application of 0.3 M citric acid to 60 cm long soil columns packed with metal‐contaminated soil. Results indicated that the uniform distribution of citric acid, applied through the subirrigation system, resulted in a more efficient extraction of metal ions. The extraction of Zn and Pb from the columns with subsurface application of citric acid was, respectively, 38 and 27 times higher than from the columns with surface application of citric acid. After washing the contaminated soil with various citric acid concentrations, the metal‐rich wash solution was treated effectively using chitosan flakes.
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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) | 0.001 | 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) | 0.001 | 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".