Granular Activated Carbon Treatment May Result in Higher Predicted Genotoxicity in the Presence of Bromide
Bibliographic record
Abstract
Certain unregulated disinfection byproducts (DBPs) are more of a health concern than regulated DBPs. Brominated species are typically more cytotoxic and genotoxic than their chlorinated analogs. The impact of granular activated carbon (GAC) on controlling the formation of regulated and selected unregulated DBPs following chlorine disinfection was evaluated. The predicted cyto- and genotoxicity of DBPs was calculated using published potencies based on the comet assay for Chinese hamster ovary cells (assesses the level of DNA strand breaks). Additionally, genotoxicity was measured using the SOS-Chromotest (detects DNA-damaging agents). The class sum concentrations of trihalomethanes, haloacetic acids, and unregulated DBPs, and the SOS genotoxicity followed the breakthrough of dissolved organic carbon (DOC), however the formation of brominated species did not. The bromide/DOC ratio was higher than the influent through much of the breakthrough curve (GAC does not remove bromide), which resulted in elevated brominated DBP concentrations in the effluent. Based on the potency of the haloacetonitriles and halonitromethanes, these nitrogen-containing DBPs were the driving agents of the predicted genotoxicity. GAC treatment of drinking or reclaimed waters with appreciable levels of bromide and dissolved organic nitrogen may not control the formation of unregulated DBPs with higher genotoxicity potencies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".