{"id":"W214799783","doi":"","title":"Getting committed: A new perspective on public transit market segmentation from two Canadian cities","year":2015,"lang":"en","type":"article","venue":"Transportation Research Board 94th Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Market segmentation; Transit (satellite); Public transport; Business; Perspective (graphical); Marketing; Customer base; Cluster analysis; Market research; Transport engineering; Geography; Computer science; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001233548,0.0005119052,0.0006715782,0.00516405,0.01878877,0.008500755,0.001932299,0.001319057,0.005296552],"category_scores_gemma":[0.003080995,0.000348766,0.0005239242,0.01226792,0.004298886,0.003640882,0.00310381,0.001799619,0.0002221614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1311098,"about_ca_system_score_gemma":0.08650717,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.997502,"about_ca_topic_score_gemma":0.9988371,"domain_scores_codex":[0.9982493,0.0002063174,0.00003039799,0.0001581911,0.0004450764,0.0009108377],"domain_scores_gemma":[0.9977251,0.0003146169,0.0001944113,0.00008027571,0.001098936,0.0005866189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0003759708,0.0003461431,0.2699259,0.0003226928,0.00007511961,0.004190595,0.5092402,0.002198416,0.002209889,0.09649195,0.02980596,0.08481721],"study_design_scores_gemma":[0.00001892873,0.00006500168,0.2756749,0.0002152898,0.00005554737,0.0003316539,0.639466,0.002408026,0.0004717474,0.003249642,0.07790651,0.000136822],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8944555,0.001408054,0.0008967405,0.009248339,0.00006644898,0.0001317554,0.001353811,0.00002708691,0.0924123],"genre_scores_gemma":[0.988997,0.0008473584,0.0005828663,0.0007117626,0.00001833215,0.00003862131,0.0006514543,0.0000226933,0.008130109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1311098,"threshold_uncertainty_score":0.951273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1212716047189682,"score_gpt":0.4207730716153991,"score_spread":0.2995014668964309,"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."}}