Comparative analysis for three different immobilisation strategies in the hexavalent chromium biosorption process using <i>Bacillus sphaericus</i> S‐layer
Bibliographic record
Abstract
Abstract Hexavalent chromium constitutes an important water pollutant due to its cancerogenic properties. In countries such as Colombia it is widely used as a preservative in the leather industry. Bacillus sphaericus S‐layer exhibits high metal‐binding capacity hence the use of this microorganism to remove metals such as chromium from polluted regions based on immobilised cells systems is suggested to be an interesting proposal. The paper describes thermodynamic adsorption process of Cr(VI) on immobilised biomass of B. sphaericus cells on polyurethane foam, sol–gel, and sawdust. The adsorption isotherms describe different immobilisation mechanisms regarding the support utilised. For example, polyurethane and sawdust immobilisation process were described with the classical Langmuir model while sol–gel followed Generalised Freundlich–Kiselev behaviour. Moreover, through determining breakthrough curves in packed columns with each medium we found surface diffusion and mass bulk transfer rate as crucial factors when scaling‐up the process.
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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 | 0.001 |
| 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".