Disinfection of recycled red‐meat‐processing wastewater by ozone
Bibliographic record
Abstract
Abstract Ozonation of a real red‐meat‐processing wastewater was conducted in a semi‐batch reactor to explore the possibility of the water reuse. The experimental results revealed that ozone was very effective in disinfection of the red‐meat‐processing wastewater. After 8 min of ozonation with an applied ozone dose of 23.09 mg min−1 liter−1 of wastewater, 99% of aerobic bacteria, total coliforms and Escherichia coli were inactivated. Empirical models were developed to predict the microbial inactivation efficacy of ozone from the CT values for the real red‐meat‐processing wastewater. A correlation was also derived to estimate the CT values from the applied ozone dose and the ozone contact time. The results also revealed that under the ozonation condition for 99% inactivation of aerobic bacteria, total coliforms and E coli, the decrease in the chemical oxygen demand and the 5‐day biological oxygen demand of the wastewater were 10.7% and 23.6%, respectively. However, ozonation under this condition neither improved the light transmission nor reduced the total suspended solids (TSS) despite of the decolorization of the wastewater after ozonation. Copyright © 2005 Society of Chemical Industry
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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) | 0.000 | 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".