Review of Critical Factors Affecting the Failure of Water Pipeline Infrastructure
Bibliographic record
Abstract
A growing population and urbanization place increased demands on water supply and distribution networks. Pipelines are one of the most critical components of water supply systems. It is, therefore, necessary to identify the relevant factors that affect the deterioration of water distribution pipelines. This will help decision makers in future planning and prioritization of the required maintenance. In this study, a systematic review is performed to identify critical factors that affect the failure of water pipelines. A meta-analysis is conducted to determine the relative importance of each factor that contributes to pipe failure. In addition, the source of contradictory results across studies is investigated. The results show that climatic factors, such as air temperature, minimum antecedent precipitation index, and net evaporation, contribute to water pipe failure. Additionally, the results of subgroup meta-analyses show that primary sources, such as pipe material and water pipe size, can lead to high heterogeneity across studies. This study is expected to help water utility owners to collect relevant data and make timely renewal decisions.
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".