{"id":"W2975866074","doi":"10.1287/mksc.2019.1187","title":"Mobile Hailing Technology and Taxi Driving Behaviors","year":2019,"lang":"en","type":"article","venue":"Marketing Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Business; Productivity; Marketing; Advertising; Mobile technology; Industrial organization; Information technology; Mobile device; Computer science; Economics; World Wide Web","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":[0.0006415658,0.00005623701,0.00005830835,0.0002861295,0.0001045892,0.00003798652,0.0001273991,0.0000313031,0.00004990681],"category_scores_gemma":[0.0000690891,0.00006019064,0.000008504502,0.001029075,0.0001595172,0.0001582058,0.00001766665,0.00009724645,0.00001375352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000240556,"about_ca_system_score_gemma":0.00001949058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002356011,"about_ca_topic_score_gemma":0.00000739554,"domain_scores_codex":[0.9994244,0.000004324585,0.0001204122,0.0001634682,0.0001113282,0.0001760948],"domain_scores_gemma":[0.9997289,0.00003360871,0.00001533191,0.000147069,0.00004489536,0.00003016675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000001237622,0.00001050188,0.4978246,0.00004123841,0.000001888658,0.000001147666,0.0003919855,0.003871354,0.4671607,0.00175721,0.00002205305,0.02891606],"study_design_scores_gemma":[0.0003602766,0.00005666009,0.9049937,0.0001627966,0.00001304762,0.00001831421,0.002125495,0.05087429,0.03145767,0.0002055213,0.00923599,0.0004962695],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944507,0.00004062818,0.0008574851,0.00002346288,0.0002012849,0.0001225227,0.000001053412,0.0003056462,0.003997184],"genre_scores_gemma":[0.9968138,0.000006818271,0.002971648,0.000011039,0.000005034021,0.00001690662,7.091102e-7,0.000006428763,0.0001676192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.435703,"threshold_uncertainty_score":0.2454503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003114607355565924,"score_gpt":0.2153157878350974,"score_spread":0.2122011804795315,"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."}}