Contaminant intrusion in water distribution networks: review and proposal of an integrated model for decision making
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
Contaminant intrusion in a distribution network (DN) refers to the entry of harmful chemicals and pathogens in the presence of three conditions: (i) the availability of a contaminant source near water mains; (ii) a pathway: leakage or breakage; and (iii) a driving force: low or negative pressure in the water main. The occurrence of contamination in a DN can take place frequently as there is no specific treatment at this stage except secondary disinfection. Contaminant intrusion requires as much attention as source water protection or treatment plants, particularly given that at this point, water is near the final stage prior to human consumption. Failure to detect and treat at this time could have potential negative impacts on consumers’ health. Following the September 11, 2001 attack, strict regulations are now enforced by the municipalities to monitor water quality within DNs. This review article focuses on various aspects of contaminant intrusion in DNs based on more than 90 journal articles, peer-reviewed conference proceedings, and research reports. Here we present details on the conditions of contaminant intrusion, water quality regulations, sampling, protection and mitigation strategies, and various modelling approaches for decision making. Based on this review, we propose an integrated model that will help guide effective decision making for contaminant detection and mitigation.
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 | 0.001 | 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 it