Wastewater Disinfection by Peracetic Acid: Assessment of Models for Tracking Residual Measurements and Inactivation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With its potential for low (if any) disinfection byproduct formation and easy retrofit for chlorine contactors, peracetic acid (PAA) or use of PAA in combination with other disinfectant technologies may be an attractive alternative to chlorine-based disinfection. Examples of systems that might benefit from use of PAA are water reuse schemes or plants discharging to sensitive receiving water bodies. Though PAA is in use in numerous wastewater treatment plants in Europe, its chemical kinetics, microbial inactivation rates, and mode of action against microorganisms are not thoroughly understood. This paper presents results from experimental studies of PAA demand, PAA decay, and microbial inactivation, with a complementary modeling analysis. Model results are used to evaluate techniques for measurement of PAA concentration and to develop hypotheses regarding the mode of action of PAA in bacterial inactivation. Kinetic and microbial inactivation rate data were collected for typical wastewaters and may be useful for engineers in evaluating whether to convert from chlorine to PAA disinfection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it