{"id":"W3092209517","doi":"10.1155/2020/8877499","title":"A Study on Public Adoption of Robo-Taxis in China","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China; China Association for Science and Technology","keywords":"Taxis; Public transport; Business; Construct (python library); China; Transport engineering; Usability; Marketing; Traffic congestion; Computer science; Engineering; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00186889,0.0003889661,0.0003909965,0.001610263,0.001877569,0.001004204,0.0004662565,0.0005838989,0.002406245],"category_scores_gemma":[0.00282521,0.0003687604,0.0007175253,0.002253515,0.0007754291,0.0009729188,0.0007108434,0.0007127193,0.0002653183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002785525,"about_ca_system_score_gemma":0.003329844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1365568,"about_ca_topic_score_gemma":0.1213363,"domain_scores_codex":[0.9990139,0.0001816232,0.00009756956,0.0001270398,0.0002685333,0.0003113627],"domain_scores_gemma":[0.9969181,0.0007718332,0.0007401385,0.0001917161,0.0007925438,0.0005857072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004943638,0.0006659921,0.9651284,0.00006474573,0.00003934472,0.0004244593,0.02459036,0.0001075102,0.0006878296,0.0002984661,0.0003231355,0.007620327],"study_design_scores_gemma":[0.000007949378,0.0001970165,0.9783972,0.00002106847,0.00002436347,0.00007338793,0.0198011,0.0005688811,0.0001466994,0.00003542901,0.000712277,0.00001465136],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995298,0.00001764185,0.00002096301,0.00005033294,0.000001126713,0.00001009983,0.00002483512,8.978089e-7,0.000344405],"genre_scores_gemma":[0.9994241,0.00006271974,0.0000332795,0.00003381228,0.000002209274,0.00001686237,0.00006221819,9.825761e-7,0.000363699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1365568,"threshold_uncertainty_score":0.2715238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02158906422558802,"score_gpt":0.2551414491344825,"score_spread":0.2335523849088945,"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."}}