Biosorption of Cr(VI) ions from aqueous solutions by a newly isolated <i>Bosea</i> sp. strain Zer-1 from soil samples of a refuse processing plant
Bibliographic record
Abstract
The adsorption behavior of Cr(VI) ions from aqueous solution by a chromium-tolerant strain was studied through batch experiments. An isolate designated Zer-1 was identified as a species of Bosea on the basis of 16S rRNA results. It showed a maximum resistance to 550 mg·L(-1) Cr(VI). The effects of 3 important operating parameters, initial solution pH, initial Cr(VI) concentration, and biomass dose, were investigated by central composite design. On the basis of response surface methodology results, maximal removal efficiency of Cr(VI) was achieved under the following conditions: pH, 2.0; initial concentration of metal ions, 55 mg·L(-1); and biomass dose, 2.0 g·L(-1). Under the optimal conditions, the maximum removal efficiency of Cr(VI) ions was found to be nearly 98%. The experimental data exhibited a better fit with the Langmuir model than the Freundlich model. The biosorption mechanisms were investigated with pseudo-first-order, pseudo-second-order, and intraparticle diffusion kinetics models. These results revealed that biosorption of Cr(VI) onto bacterial biomass could be an alternative method for the removal of metal ions from aqueous solution.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".