An integrated framework to sustainable and resilient infrastructure design and management in a changing climate
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
Climate change driven by human activities is causing significant warming, with further increases anticipated. These changes pose unprecedented risks to Canada’s core public infrastructure, including hospitals, roads, bridges, and water systems, with profound implications for public safety, health, security, equity, environmental conservation, and economic prosperity. Minimizing infrastructure failure requires integrating sustainability and resilience principles into decision-making for both new and existing assets. A review of current practices highlights notable gaps, particularly the limited integration of climate change mitigation and adaptation efforts. To address these challenges, a novel integrated framework is proposed, combining mitigation and adaptation strategies with Life Cycle Thinking methods—specifically, Life Cycle Performance (LCP), Life Cycle Assessment (LCA), Life Cycle Cost Analysis (LCCA), and Social Life Cycle Assessment (S-LCA). This framework offers a comprehensive approach to enhancing infrastructure sustainability and resilience, supporting the selection of sustainable designs and effective management strategies in the context of a changing climate.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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