Multicriteria Optimization of a Chemical Leaching Process for Sewage Sludge Decontamination
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sewage sludge decontamination requires the removal of toxic metals and it can be performed by chemical leaching. The commercialization of such a decontamination process needs to consider the preservation of the sludge fertilizing properties and the ease of dewatering of the acidic treated sludge. Moreover, operating costs must be acceptable under optimal operational parameters. Chemical leaching assays were performed at the laboratory bench scale with biological sludge. Afterwards, a multicriteria analysis has been conducted to determine the optimal operational parameters allowing the sludge decontamination while meeting all performance criteria. The analysis pointed out adequate working ranges in terms of sulfuric acid, ferric chloride, and hydrogen peroxide concentrations to be used for chemical decontamination of the sludge. Moreover, it allowed establishing a mathematical equation to help identify the optimal working range for further studies having different contamination scenarios.
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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 it