Treatability of 18 taste and odor compounds in drinking water using oxidation
Bibliographic record
Abstract
Abstract The occurrence of taste and odor (T&O) compounds in drinking water can lead to public concern about quality when left unaddressed, therefore suitable treatment is needed. This study evaluated the treatability of 18 T&O compounds using chlorine, permanganate, and ozone in MilliQ and river water. Nine T&O compounds showed complete oxidation (>99% removal) in all water matrices by ozone. Most of the remaining T&O compounds were removed to >50% by ozone. Alkalinity, pH, and natural organic matter (NOM) had a significant impact on the decay of ozone. Chlorine and permanganate were ineffective (removal <30%) for 2‐methylisoborneol (2‐MIB), geosmin, hexanal, pyrazines, and haloanisoles. Although chlorine achieved complete removal for alkyl sulfides and indole, it was only partially effective for aldehydes and ketones. Permanganate was more effective than chlorine in oxidizing unsaturated aldehydes and ketones. Increased NOM and pH reduced oxidation effectiveness for chlorine, but not permanganate.
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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 | 0.000 | 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".