Forensics of water quality failure in distribution systems - a conceptual framework
Bibliographic record
Abstract
Precise causes of water quality failures are often difficult to pinpoint. The complexity of the distribution system (many kilometers of pipes of different materials and ages), occurrences of physical/chemical/biological processes and the lack or absence of timely data make forensic analyses of water quality failure events very challenging. Water quality failure in the distribution system can occur through several pathways. These include intrusion of contaminants through failed or compromised pipes and cross-connections, regrowth of microbes in pipes and distribution storage tanks, leaching of chemicals or corrosion products from system components (pipes, tanks, liners), water treatment failure, deliberate contamination by terrorists and permeation of organic compounds through various plastic components of the system. Various indicators of water quality failure (symptoms) such as changes in the turbidity, odour, taste and colour, waterborne illnesses ranging from minor to serious, etc. can provide clues as to the causes of the failure in much the same way as symptoms of human health are used to diagnose causes and propose treatment.
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.
How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".