National Survey on the Trends in Small-Diameter Water Pipeline Failures
Bibliographic record
Abstract
A national survey was conducted during the years 2008-09 by the Center for Innovative Grouting Materials and Technology (CIGMAT) at the University of Houston in collaboration with the City of Houston to document the conditions of small-diameter (< 500 mm diameter) water pipelines in the United States and Canada. Several major cities and few smaller cities participated in the survey, representing a population of 11 million and a water pipeline length of more than 28,000 mi with pipe diameters less than 500 mm. The survey results were analyzed with number of local parameters to establish the general trends observed in the water pipeline failures. The results were also compared with the one conducted by the U.S. Mayor in 2007. The survey conducted by U.S. Mayor included more than 290 cities, representing a population of more than 30 million with water pipeline length of more than 100,000 mi. By comparing the two surveys, the CIGMAT survey represented somewhat larger water systems with several cities having total water pipeline length greater than 1,000 mi. Based on both surveys, the water pipeline breaks per day varied from 0.002 to 12. From the CIGMAT survey, it was possible to investigate the relationship between water pipeline breaks or breaks per mile with numbers of independent variables and the total pipe length in a city was an important parameter. In this study, few relationships were developed for water pipeline breaks using the CIGMAT survey data and the predictions were compared with the USCM survey data.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.002 | 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".