Full‐Scale Ozone–Biofiltration: Seasonally Related Effects on NOM Removal
Bibliographic record
Abstract
Performance of full‐scale ozone–biofiltration was investigated over 14 months to determine the potential effects of seasonally related changes in water temperature and quality on the removal of natural organic matter fractions. The biofilters removed on average 12% of dissolved organic carbon, 31% of biopolymers, 6% of humic substances, 10% of humic building blocks, 31% of low‐molecular‐weight (LMW) acids/LMW humics, 14% of LMW neutrals, and 52% of assimilable organic carbon. The biofilters exhibited an increase in removal of dissolved organic carbon, biopolymers, LMW acids/LMW humics, and assimilable organic carbon as temperature increased from 3 to 28°C, even though filter contact time was somewhat shorter at higher temperatures. Although phosphorus concentrations were reduced by coagulation pretreatment, the biofilters effectively removed the LMW compounds generated from ozonation. Filter biomass levels were not related to temperature, empty bed contact time, time during the filter cycle, or removal of natural organic matter.
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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".