Effect of Sonication on UV Disinfectability of Primary Effluents
Bibliographic record
Abstract
In this paper, the effect of sonication on the UV disinfection kinetics of primary effluents was investigated. Wastewater samples were collected from local municipal treatment plants and were sonicated with a 20-kHz ultrasound reactor at constant power but varying sonication times. Sonicated samples were irradiated using low-pressure UV light to obtain the UV dose-response curves (DRC). Results showed that sonication improved the UV disinfection of primary effluents by (1) increasing the initial slope of DRC (i.e., k1) and (2) decreasing the tailing level of the UV dose-response curve (i.e., beta). This improvement was confirmed to be caused by the breakage of large particles (> 60 microm) that are known to protect coliforms from UV photons. It also was found that the log reduction of the tailing level of DRC was directly proportional to the log reduction of the number of large particles (> 60 microm) present in the effluent sample. Although the number of large particles was proportional to the coliform count at high UV dosage, the proportionality constant varied from 0.05 to 0.25, depending on the sample.
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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 | 0.002 |
| 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 | 0.000 | 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".