Decision Making Process for the Most Appropriate Pipe Rehabilitation Method by Holistic Evaluation Technique
Bibliographic record
Abstract
A significant percentage of the pipelines in the United States were installed in the early to mid-20th century, and many still in service have exceeded their intended design life. As a result, there are significant needs for pipeline rehabilitation or renewal. Selecting an appropriate rehabilitation methodology is a complex decision in which pipe material, diameter, and design loading must be considered. The primary drivers in determining the most appropriate rehabilitation or replacement method include cost, scheduling, service life of the repair, impacts to existing operations, constructability, impacts to surrounding communities, surface preparation, allowable diameter reduction, safety, and the ability to accommodate misalignments. The Westminster Boulevard Force Main Replacement project, currently under construction, involves the replacement of two parallel sewer force mains using a combination of open trench, slip-lining, and cured-in-place-pipe (CIPP). These technologies were carefully selected after considering numerous technologies and demonstrate that a holistic approach to choosing a rehabilitation method assists owners and engineers in making better informed decisions.
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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 | 0.025 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".