A scenario simulation approach for sustainable mobility project evaluation based on fuzzy cognitive maps
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
Sustainability evaluation of new urban mobility projects is a challenging decision due to the presence of multiple objectives (social, economic, environmental), limited data availability, presence of multiple stakeholders, and specific context of each city. Scenario modeling and simulation is a useful tool to address such situations. In this paper, we present a fuzzy cognitive mapping-based scenario simulation approach for evaluating sustainable mobility projects. Linguistic assessments and fuzzy set theory are used to address the uncertainty arising from lack of quantitative data. The criteria for sustainability evaluation are obtained using fuzzy Delphi technique. A numerical application is provided for the city of Luxemburg. The strength of the proposed approach is the ability to aid in decision-making of new sustainable mobility project evaluation and selection under limited or no quantitative data availability. In addition, it is able to deal with multiple, co-related and conflicting criteria in evaluation.
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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) | 0.000 | 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 | 0.001 |
| 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