Disinfection of Hospital Wastewater by Continuous Ozonization
Bibliographic record
Abstract
The disinfection of hospital wastewaters using the ozonization process was studied. The concentrations of ozone required to reach a sudden drop of coliform and Pseudomonas aeruginosa in the wastewater are 4.0-7.0 and 3.0-5.0 mg L(-1), respectively. For the hospital wastewater, the disinfection efficiencies were 0.518S(-1.1) for coliforms, 0.509S(-1.06) for Pseudomonas aeruginosa and 0.254S-(1.54) for total count, respectively. As to the effects of ozone input methods on the disinfection efficiency, the continuous ozonization process was ten times higher than the batch input process. The low COD removal rate was obtained at 25.0 mgL(-1) of ozone concentration for hospital wastewater. However, more biodegradable compounds resulted in the treated mixture.
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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 | 0.001 | 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".