Effect of cleanup of spiked sludge on corn growth biosorption and leaching of metals
Bibliographic record
Abstract
A bstract A chemical leaching process has been used for the cleanup of two municipal biosolids (MOS and BES) spiked with Cd, Cu, Zn or their mixture prior to agricultural use. Non-cleaned, cleaned and washed biosolids were compared as soil amendments for corn cultivation inside glasshouse. Corn growth, biosorption of metals and leaching of these metals in leachate were measured. Results showed that biosolid amendments tend to produce more aerial biomass. Cleanup and washing of BES biosolid significantly augmented total biomass of roots and stalks, respectively. Regarding biosorption of metals, Cd could not be found neither in corn seeds, nor in stalks, while slight amounts of Cu were detected. Whereas Cd and Cu diminished in the order roots > leaves > stalks, Zn diminished from leaves > roots > stalks. Cleanup and washing of MOS and BES biosolids significantly lowered biosorption of Cd, Cu, Zn, and other metals. Leaching into the outlet water varied with time, but average concentrations were moderately low. There were significant amounts of metal leached from MOS biosolid. The effects of cleanup and washing of both biosolids on biosorption and leaching depended on the initial metallic charge and the biosolid type.
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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 | 0.000 | 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".