Indicators and framework for assessing sustainable infrastructure
Bibliographic record
Abstract
Much of the focus on sustainable infrastructure has concentrated on buildings and construction processes. To advance this thinking for other civil infrastructure systems (CIS), this paper outlines a framework that uses a set of proposed indicators to measure the sustainability of chosen infrastructure options and help select the preferred alternative in a multiobjective decision approach. Physically implementing "sustainable infrastructure" involves three life stages for any project: preproject planning, project implementation, and ongoing operations. It is critical to evaluate the sustainability of chosen options in each of these life stages. This research develops two categories of indicators, mandatory screening indicators (MSI) and judgment indicators (JI), and a multilayer approach for incorporating these indicators. A normalization procedure has been adapted to work within the framework to help compare alternatives across a range of indicators and different orders of data magnitude. A hypothetical example using a transmission line corridor is presented to illustrate how the framework can be applied.Key words: indicators, infrastructure, sustainable, environment, decision making, alternatives.
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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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".