Removal of copper from contaminated waters using rhamnolipids
Bibliographic record
Abstract
The use of rhamnolipids constitutes an attractive and eco-compatible alternative in the remediation of contaminated environments with heavy metals. In the present work, the ability of rhamnolipid produced by P. aeruginosa ORA9 to remove copper in contaminated waters of the Blue Lagoon of El Cobre, was evaluated, to control and reduce the human and environmental risk that these waters represent. The influence of the pH of the rhamnolipid solution (4-10), the contact time (2-10 hours) and the concentration of the biosurfactant (40- 120 mg L-1) in the process were studied, through a factorial design Box-Bhenken. An increase in the percentage of copper removal proportional to the contact time and the concentration of the biosurfactant was observed, reaching 48% removal at 10 h and 120 mg L-1. The results obtained indicate that rhamnolipids can be used in the design of a technology to remove copper in polluted contaminated waters.
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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".