Bioleaching of copper and other metals from low‐grade oxidized mining ores by <i>Aspergillus niger</i>
Bibliographic record
Abstract
Abstract A study was initiated to determine the feasibility of using the fungus Aspergillus niger for bioleaching metals from oxide low‐grade ore. Large quantities of the metals are embodied in the low‐grade ores and mining residues that can be recovered. Presently available techniques (pyrometallurgical and hydrometallurgical) are expensive or may have a negative impact on the environment. An oxidized mining ore containing mainly copper (7245 mg kg−1 residue) was studied. In this study, the fungus A niger produced a variety of organic acids. Addition of small quantities of sulfuric acid enhanced the organic acids, efficiency. Various agricultural wastes were evaluated as substrates and a maximum solubilization of 68% for copper for a medium containing potato peels was achieved. In conclusion, leaching of copper from a mining ore is technically feasible using A niger. Further research must be performed to increase the rate of copper removal. Copyright © 2003 Society of Chemical Industry
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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) | 0.000 | 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".