Increasing Pipelines’ Resilience for a Changing Climate
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
Climate change, population growth, plastic pollution, tight budgets, and energy cost are posing sustainability challenges to our water and wastewater management systems. Standard engineering practices aim to provide reliable engineering designs that allow water and wastewater pipelines to tolerate typical loading conditions. However, failures are occurring due to natural disasters and extreme weather conditions. These events emphasize the need for resilient, sustainable performance-based engineering practice to ensure impacts on pipelines are minimized, recovery is quick, and functionality is maintained in the long term, while considering the consequences for society, the global economy, and the environment. This paper discusses the threats to water and wastewater pipelines due to natural disasters and aspects of ductile iron pipe that contribute to its resilience. The crucial role of resilient materials in reducing their impact on infrastructure response is discussed, including the ramifications to economic, health, and safety hazards that may result from poor decisions made without consideration of key factors such as sustainability and resilience.
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 | 0.000 | 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 it