Investigation of the formation of <scp>NDMA<sub>UFC</sub></scp> across biofilters
Bibliographic record
Abstract
Abstract Full‐scale sampling at 16 facilities illustrated that NDMA precursor concentrations, measured by adding chloramine under Uniform Formation Conditions (NDMAUFC), increased across biofiltration at 7 of 16 facilities (by 3–48 ng/L or 12%–296%) but stayed the same or decreased (by up to 5 ng/L or 24%) at the other nine facilities. Increases in NDMAUFC concentrations were attributed to both particulate and soluble precursors. Only two facilities had an increase in NDMAUFC greater than 10 ng/L. However, NDMAUFC concentrations in the biofilter effluent from five facilities exceeded 10 ng/L during one or more sampling events. For these facilities, testing at multiple scales showed that mitigation steps could include pretreatment with ozone (which resulted in overall lower NDMAUFC), increased free chlorine contact time prior to ammonia addition, and/or optimized biofilter design and operation.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".