{"id":"W3172683300","doi":"10.1109/tits.2021.3082767","title":"Urban Air Mobility: History, Ecosystem, Market Potential, and Challenges","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Air Traffic Management and Optimization","field":"Engineering","cited_by":497,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Toyota Motor Corporation; National Aeronautics and Space Administration","keywords":"Aviation; Business; Sustainability; Metropolitan area; Business model; Ecosystem services; Transport engineering; Engineering; Marketing; Geography; Ecosystem","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001782324,0.000253341,0.000277907,0.0001893316,0.0000843389,0.00003198022,0.00008559461,0.0001418557,0.0003996062],"category_scores_gemma":[0.000001041682,0.0002855528,0.0001181828,0.0001452199,0.00002677775,0.0002101229,2.076774e-7,0.0001594213,0.00003402596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002018467,"about_ca_system_score_gemma":0.00002640186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001639151,"about_ca_topic_score_gemma":0.0002697932,"domain_scores_codex":[0.9985252,0.00007164344,0.0005357133,0.0003698966,0.0002783633,0.0002191661],"domain_scores_gemma":[0.9993899,0.00004641043,0.00005591387,0.0002814016,0.0001135425,0.0001127644],"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":[0.00002982786,0.0001490196,0.00001590934,0.001572679,0.0002256636,0.00003168301,0.001516928,0.9854134,0.000114484,0.0005423134,0.003503326,0.006884807],"study_design_scores_gemma":[0.0008591052,0.0001429499,0.0008205632,0.0005894158,0.0003564529,0.00002880594,0.005039152,0.6765051,0.004839351,0.00001355399,0.3098409,0.0009646508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008199147,0.009035152,0.9752907,0.0001120445,0.003173709,0.0005602596,0.00009160923,0.0006790604,0.002858382],"genre_scores_gemma":[0.9854054,0.01198505,0.0001805023,0.00002156414,0.00006719089,0.0001493443,0.00004640335,0.00005380829,0.002090768],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9772062,"threshold_uncertainty_score":0.9999596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02020842371448392,"score_gpt":0.1900098583928744,"score_spread":0.1698014346783905,"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."}}