{"id":"W2067997433","doi":"10.1007/s40565-015-0112-4","title":"Multi-agents modelling of EV purchase willingness based on questionnaires","year":2015,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Energy, Environment, and Transportation Policies","field":"Energy","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Engineering and Physical Sciences Research Council; State Grid Corporation of China; National Natural Science Foundation of China","keywords":"Computer science; Operations research; Business; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003837635,0.0002024142,0.0003949399,0.0001725965,0.00006018727,0.00003212678,0.0001533754,0.0001139877,0.00000854415],"category_scores_gemma":[0.00002075564,0.0001663943,0.0001281215,0.00007804506,0.00007645966,0.000177282,0.000007614281,0.0001135347,0.000001091441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005122462,"about_ca_system_score_gemma":0.00006199901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00205167,"about_ca_topic_score_gemma":0.0001706676,"domain_scores_codex":[0.9982459,0.0001146558,0.0007346763,0.0001739699,0.0005288587,0.0002019624],"domain_scores_gemma":[0.9987133,0.00004396211,0.000593228,0.0002175166,0.0001718051,0.0002602454],"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":[0.0001545631,0.0002346294,0.0006939318,0.00003371297,0.00007139688,0.00002670766,0.0008919199,0.9874787,0.000278976,0.008198381,0.00008600471,0.001851035],"study_design_scores_gemma":[0.003419413,0.0006036339,0.001616994,0.0005785165,0.00009135075,0.00003802248,0.0008387741,0.9751245,0.002589417,0.00117547,0.01358013,0.000343757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.395441,0.002498502,0.5999534,0.00008525997,0.000779371,0.00004563756,0.0000138954,0.00002204789,0.001160934],"genre_scores_gemma":[0.9985148,0.0002855834,0.0005635,0.0001315364,0.0001018559,0.000003629676,0.000006190178,0.00003974547,0.0003531861],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6030738,"threshold_uncertainty_score":0.6785364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04302193870899376,"score_gpt":0.2495337327964161,"score_spread":0.2065117940874223,"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."}}