Size Characterization of Biofiltration-related N-nitrosodimethylamine (NDMA) Precursors
Bibliographic record
Abstract
Previous studies have reported variable removals or even contributions of N-nitrosodimethylamine (NDMA) precursors during biofiltration. To better understand the source of these biofiltration-related NDMA precursors, it is imperative to quantify their state (i.e., dissolved or particulate). This study characterized biofiltration-related NDMA precursors according to their size as well as quantified their removal by examining them in backwash remnant water. Biofiltration-related particulate precursors were the primary contributor (43-64%) to the total NDMA precursor level in the influent, while dissolved precursors were the dominant size fraction (56-83%) in the effluent. Although near-complete removal (80-91%) of particulate precursors was observed during filter ripening, dissolved precursors were removed to a lesser extent (22-31%), indicating their greater potential for a breakthrough. In the event of a breakthrough of dissolved NDMA precursors, turbidity may not be an effective parameter to evaluate backwash performance.
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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".