Real-time detection of water quality aberrations in a water distribution system
Bibliographic record
Abstract
This thesis is an investigation of the vulnerability of a water distribution system to contamination and the potential to mitigate the harmful effects of a contaminant by the use of a contaminant warning system. Potential causes for water quality degradation include, but are not limited to, purposeful attack, back flow in conjunction with a cross connection or cracked watermain, new or repaired watermains, finished storage water facilities, and inadequate separation of water and sewage lines. To ensure water quality in the distribution system is maintained, there are ongoing efforts focused on development of continuous, online detection systems. The systems being developed consist of two parts; a primary system used to initially detect a contamination, consisting of an algorithm that is sensitive enough to detect false positives but trigger an alarm when a contamination is suspected and a confirmatory system that can ensure a contamination has actually occurred. Free chlorine, total chlorine, turbidity, pH, conductivity and TOC have been selected as primary sensors for determining water quality. These instruments are inexpensive and have the capability to operate online and in real-time. The MFI Brightwell assay, the ATP from LuminUltra assay and the spectral fluorescence signature from LDI3 assay have been selected as possible confirmatory systems. The S::can turbidity sensor showed a statistically significant increase in NTU value when 'E. coli' K12 in Milli-Q water was added to tap water at a concentration of greater than 103 CFU/mL. ' E. coli' K12 in-phosphate buffer added to tap water was detected by a free chlorine sensor at concentrations between 9.9x10 4 CFU/mL and 8.8x105 CFU/mL, by a turbidity sensor at cell concentrations between 6.4x104 CFU/mL and 4.3x10 6 CFU/mL, by a nTOC sensor at a concentration of 6.4x105 CFU/mL and by a conductivity sensor at concentrations between 4.1x10 5 CFU/mL and 4.0x106 CFU/mL. This limited the risk of infection of an adult to between 52% and 23%, depending on the amount of free chlorine present in the distribution system. Furthermore, the presence of pathogens in tap water was confirmed, when the chlorine residual was removed, at a concentration of 98 CFU/mL. With increased instrument sensitivity, the reduction of the false positive rate and new methods for ensuring detections, contaminant warning system could soon be a viable option for water protecting public drinking water.
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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 | 0.000 | 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".