Bibliographic record
Abstract
Like most utilities in North America, the City of Regina (City) is facing the challenge of aging infrastructure, including a high rate of annual water main breaks. Repair of the breaks is becoming a notable maintenance concern for the City, as it consumes a significant portion of the City’s maintenance fund. Water main breaks may also be an inconvenience to residents and businesses, and even interrupt the operation of vital services, such as fire-fighting operations. Cured-in-place pipe (CIPP) rehabilitation was one of the options that the City had investigated to proactively rehabilitate the water mains. In 2010, the City started a CIPP pilot project. Since then, the City has relined approximately 21 km of water mains, primarily for small diameter asbestos cement pipes. This paper reviews the relining work, including the challenges and issues faced by the City during quality control practice. The performance of the liners since the pilot work in 2010 is also evaluated, including a detailed analysis of 12 leaks that occurred to the water mains relined by CIPP. Overall, the liners are serving their intended purpose and improving the performance of the City’s water system by mitigating the “ hot spots.” Detailed analysis of the leaks indicates issues that may be faced by other CIPP users, and that need to be improved by CIPP contractors and manufacturers. The retrospect may benefit those utility owners that are looking for alternative options to open cut to rehabilitate their linear water infrastructure.
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 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".