{"id":"W4206266580","doi":"10.3390/su14020715","title":"Smart Urban Mobility System Evaluation Model Adaptation to Vilnius, Montreal and Weimar Cities","year":2022,"lang":"en","type":"article","venue":"Sustainability","topic":"Smart Cities and Technologies","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"TOPSIS; Analytic hierarchy process; Ranking (information retrieval); Weighting; Multiple-criteria decision analysis; Computer science; Operations research; Performance indicator; Artificial intelligence; Engineering; Business","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009597848,0.0001543813,0.0001896188,0.0001179778,0.0002740733,0.00003703186,0.0001368657,0.00005767437,0.00002264037],"category_scores_gemma":[0.0002463995,0.0001699119,0.00004569029,0.000228832,0.00006733475,0.0001394107,0.0001918902,0.0001764752,9.27003e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002648973,"about_ca_system_score_gemma":0.0001440675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009652319,"about_ca_topic_score_gemma":0.0002178248,"domain_scores_codex":[0.9987196,0.00009972579,0.0002476143,0.0003025057,0.0003430026,0.0002876045],"domain_scores_gemma":[0.9991299,0.00006345491,0.00002684211,0.0004231113,0.0002968201,0.00005988462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005452776,0.0000377683,0.007244925,0.0005588755,0.00002532383,0.00000261914,0.004318974,0.9576854,0.00002129698,0.007565279,0.001348839,0.02113615],"study_design_scores_gemma":[0.000229255,0.00008311374,0.02223725,0.000004183526,0.00002646307,0.000002994495,0.042494,0.920939,0.00005096917,0.01309123,0.000659398,0.0001821236],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9895778,0.0004193428,0.006185182,0.0002949761,0.0001884535,0.001155516,0.00005993426,0.0009185892,0.001200176],"genre_scores_gemma":[0.9984987,0.000004171018,0.0003503526,0.00001530471,0.00002247699,0.0009884363,0.00002009964,0.00001921288,0.00008126221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03817503,"threshold_uncertainty_score":0.6928807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01197154435932763,"score_gpt":0.2197863424634692,"score_spread":0.2078147981041416,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}