Navigating Climate Variability for the Pursuit of Transportation Infrastructure Sustainability: A Systematic Review
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
The increasing frequency and severity of climate variability poses substantial challenges to the sustainability and reliability of transportation infrastructure worldwide. Transportation systems, vital to economic and social activities, are highly vulnerable to extreme weather, sea-level rise, and temperature fluctuations, which can disrupt their structural integrity, operational efficiency, and maintenance needs. The aim of this study is to explore the scholarly landscape concerning the effects of climate variability on transportation systems, analyzing 23 years of scientific publications to assess research trends. Utilizing bibliometric methods, this analysis synthesizes data from numerous scientific publications to identify key trends, research hotspots, influential authors, and collaborative networks within this domain. This study highlights the growing acknowledgment of climate variability as a crucial factor affecting the design, maintenance, and operational resilience of transportation infrastructure. Key findings indicate a notable increase in research over the last decade, with a strong focus on the effects of extreme weather events, sea-level rise, and temperature changes. The analysis also shows a multidisciplinary approach, incorporating perspectives from civil engineering, environmental science, and policy studies. This comprehensive overview serves as a foundational resource for researchers and policymakers, aiming to enhance the adaptive capacity of transportation systems to climate variability through informed decision-making and strategic planning.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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