{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001412756,0.0009958887,0.0003933421,0.001867687,0.0008034552,0.001842868,0.001267289,0.0005724014,0.004654204],"category_scores_gemma":[0.001706829,0.0002481591,0.001131151,0.001722347,0.0004773886,0.0007640819,0.0009773704,0.0004872147,0.0005107805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008827232,"about_ca_system_score_gemma":0.005565505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4419158,"about_ca_topic_score_gemma":0.3941415,"domain_scores_codex":[0.9992738,0.0003067489,0.00002485705,0.0001238272,0.0001332607,0.0001374291],"domain_scores_gemma":[0.9995219,0.00009821916,0.00004088827,0.00001883225,0.0002856707,0.00003456047],"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":[0.0001138637,0.0001344849,0.009731481,0.0001618674,0.0001032988,0.0003556459,0.0003735602,0.9335899,0.001093583,0.01621637,0.003770461,0.03435548],"study_design_scores_gemma":[0.00001868673,0.00007601465,0.005545169,0.00002788332,0.00004532087,0.00002485698,0.0003212555,0.98702,0.0003188771,0.00166231,0.004916389,0.00002324969],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5439828,0.00152828,0.3475417,0.001157616,0.0002198522,0.002567852,0.003890072,0.001744039,0.09736782],"genre_scores_gemma":[0.9287517,0.0009191512,0.04723719,0.0000578693,0.00002393418,0.001153205,0.00178516,0.00009063048,0.0199812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4419158,"threshold_uncertainty_score":0.8786872,"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."}}