Multi-Criteria Decision Making for Multi-Purpose Utility Tunnel Location Selection
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
Repeated excavations of buried utilities cause road congestion, maintenance conflicts, and subsequently increase social costs. An alternative of burying utilities is hosting them in a multi-purpose utility tunnel (MUT). MUTs reduce the excavation needs and provide easy access for all year-round inspection and maintenance for utilities. MUT planning is a key factor of urban underground space planning. Previous research focused on MUT technologies; however, few papers focused on MUT planning. Location selection for MUTs is an important phase for MUT planning and it is complicated because it depends on several criteria. This paper provides a general method for MUT location selection at different urban scales using geographic information system (GIS) and multi-criteria decision making (MCDM) for the selection of potential MUT locations. The weights of the criteria are calculated using the analytic hierarchy process (AHP) method. A case study is used to demonstrate the feasibility of the proposed method.
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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 | 0.001 |
| 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