{"id":"W2791932334","doi":"10.1080/02286203.2018.1451711","title":"A scenario simulation approach for sustainable mobility project evaluation based on fuzzy cognitive maps","year":2018,"lang":"en","type":"article","venue":"International Journal of Modelling and Simulation","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Fuzzy cognitive map; Fuzzy logic; Sustainability; Computer science; Context (archaeology); Delphi method; Fuzzy set; Set (abstract data type); Management science; Operations research; Fuzzy number; Engineering; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.00169622,0.001040394,0.0007591611,0.002342227,0.0009765658,0.001733613,0.001356851,0.00114145,0.003464622],"category_scores_gemma":[0.002811098,0.0004557343,0.001346051,0.001673722,0.0007340868,0.00128675,0.00162988,0.0008497653,0.0002306844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002046185,"about_ca_system_score_gemma":0.001887555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01187927,"about_ca_topic_score_gemma":0.01119404,"domain_scores_codex":[0.998755,0.0008016917,0.00005027944,0.00009010976,0.000221646,0.00008132225],"domain_scores_gemma":[0.9988434,0.0007384842,0.00007491856,0.00006237513,0.0001996093,0.00008125062],"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":[0.00003889078,0.00004751602,0.0004774452,0.00006897794,0.00006039979,0.0001437591,0.0002648146,0.945785,0.0008905066,0.03720936,0.000355017,0.01465832],"study_design_scores_gemma":[0.000009093673,0.00002310785,0.00009813668,0.00001228473,0.00001322603,0.0000237054,0.00006550449,0.9886198,0.0002088561,0.009891006,0.001021722,0.00001348676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02565589,0.0001453595,0.9625601,0.0002214883,0.00003561333,0.0002484051,0.000127882,0.0002083421,0.01079696],"genre_scores_gemma":[0.5808629,0.0003408399,0.4151384,0.00005442408,0.00002235636,0.001004302,0.0001950257,0.0000514192,0.002330294],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01187927,"threshold_uncertainty_score":0.02362025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08849873360582923,"score_gpt":0.3664141558573408,"score_spread":0.2779154222515116,"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."}}