{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004870781,0.0002712335,0.0002180004,0.0007511628,0.0005342904,0.001585459,0.00028592,0.0006071739,0.004292581],"category_scores_gemma":[0.005020783,0.0001676862,0.0006213682,0.0008310407,0.0003414418,0.0006135002,0.0005386437,0.0009435401,0.0007064827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007178287,"about_ca_system_score_gemma":0.0005511955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01915375,"about_ca_topic_score_gemma":0.02057875,"domain_scores_codex":[0.9994451,0.0002110507,0.00003176737,0.00006877127,0.0001267879,0.0001164973],"domain_scores_gemma":[0.9938912,0.002243797,0.002104676,0.0001710882,0.0005762503,0.001012866],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002948901,0.0008564514,0.9894835,0.00004212489,0.0001496181,0.00007926737,0.000711702,0.0002156602,0.0005209668,0.0001589314,0.0001534169,0.00733331],"study_design_scores_gemma":[0.000005027578,0.0003826923,0.9968605,0.0000157634,0.00008709035,0.00006720721,0.001305274,0.0004255192,0.0001870807,0.000062728,0.0005936074,0.00000758703],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968309,0.0001888303,0.0001016711,0.00009909426,0.000009812213,0.00001463077,0.000122082,0.000003932054,0.002628979],"genre_scores_gemma":[0.9976414,0.0001978454,0.0001532912,0.00002825626,0.00001138874,0.00001275576,0.0001378407,0.000002653021,0.001814434],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01915375,"threshold_uncertainty_score":0.03808451,"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."}}