A comprehensive approach to long and short term planning of water main renewal
Bibliographic record
Abstract
Efficient renewal planning of water mains requires the consideration of the long term deterioration of their structural resiliency, their deteriorating hydraulic capacity and their life-cycle costs. Cost of pipe replacement can be significantly affected by economies of scale and by coordinating pipe replacement with adjacent infrastructure work such as roads, sewers, etc. The simultaneous consideration of all these factors at a single pipe planning resolution is computationally prohibitive due to vast dimensionality. In this paper we present a comprehensive approach that considers these factors in two stages. In the first stage, the long-term deterioration of both the structural resiliency and hydraulic capacity of water mains are explored, along with the consequences of failure and renewal cost, to produce a list of candidate pipes to be considered for renewal in the short-term. In the second stage, these candidate pipes are examined in more detail, including economies of scale and adjacent infrastructure consideration, to produce the best candidates for immediate and near-term action.
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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".