Combined MBBR‐MF for industrial wastewater treatment
Bibliographic record
Abstract
Abstract An assessment of the performance of a combined moving bed biofilm reactor and a membrane filtration (MBBR‐MF) system for treatment of a wastewater from a potato chip factory was performed. Pretreatment of membrane feed by coagulation with alum, ferric chloride, and a blend of polyaluminum chloride and polyamine was investigated for improving membrane performance. The effect of coagulation on membrane fouling was found to strongly depend on the type and dosage of the coagulant and the MBBR effluent characteristics. Ferric chloride performed the best as a pretreatment coagulant compared with alum and the coagulant blend. It reduced total fouling by 79% and increased consistency as compared with the other coagulants. Alum and the blend were, on average, 30% and 8%, less effective than ferric chloride in reducing total fouling. © 2011 American Institute of Chemical Engineers Environ Prog, 2011
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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) | 0.001 | 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 | 0.001 |
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".