The Impact of Natural Variation of OH Radical Demand of Drinking Water Sources on the Optimum Operation of the UV/H<sub>2</sub>O<sub>2</sub> Process
Bibliographic record
Abstract
Hydroxyl radical (•OH) water demand is a key parameter which impacts the design and operation of UV/H 2 O 2 process for water treatment. Long-term monitoring of the •OH water demand in water sources used for drinking water production indicated significant seasonal variations of this parameter (1.59 × 10 4 to 4.98 × 10 4 s –1 ), which coincided with the occurrence of algal blooming events. Pilot-scale tests at a drinking water treatment plant confirmed that the UV/H 2 O 2 process performance for contaminant removal is predictable when the •OH water demand is accurately determined through a validated experimental method. A predictive tool was developed to identify the optimum operating conditions of the UV system with the UV/H 2 O 2 process and it was used to demonstrate the significant impact of seasonal variations of •OH water demand on the operating costs.
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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 | 0.001 |
| 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".