Survival Rate Analyses of Watermains: A Comparison of Case Studies for Canada and Iran
Bibliographic record
Abstract
Frequent watermain failure is a major challenge for water utilities around the world.A quantitative picture of failure time, and the rate of failure for different types of watermains, provide the opportunity for utilities to implement efficient proactive asset management strategies to minimize the overall cost of operations.The Kaplan-Meier survival analysis is carried out for the time-to-failure in the watermains in two different case studies, one in Canada and one in Iran.At first, the times between failures for each material of watermains were estimated.Then, the rates of survival for the predominant pipe materials, namely cast and ductile iron, are compared.In both data sets, cast iron pipes show fast deterioration rates relative to other types of pipe materials.The results demonstrate that cement mortar lined (CML) pipe and cathodic protection (CP) are generally promising for improving the life expectancy of metal watermainsFrom the engineering point of view, the results provide asset management information for rehabilitation scenarios based on a list of priority parameters.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".