{"id":"W4327739343","doi":"10.1177/03611981231156920","title":"Who is Buying SUVs and Light Trucks in Montreal? A Factor and Cluster Analysis","year":2023,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Arup Group (Canada); McGill University","funders":"","keywords":"Truck; Metropolitan area; Externality; Transport engineering; Cluster (spacecraft); Business; Traffic congestion; Marketing; Public economics; Geography; Economics; Engineering; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0009660941,0.0002988264,0.0003030144,0.001476802,0.0019752,0.00200407,0.0008554588,0.0004221105,0.003468693],"category_scores_gemma":[0.003149486,0.0002376137,0.0005268623,0.002641129,0.0009669736,0.0006178663,0.000703259,0.0005739986,0.0002351515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01226596,"about_ca_system_score_gemma":0.00922366,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9698565,"about_ca_topic_score_gemma":0.9790922,"domain_scores_codex":[0.9991542,0.0001875498,0.00002655389,0.0001414521,0.0001874064,0.00030281],"domain_scores_gemma":[0.9987551,0.0002152294,0.0002411014,0.00005730085,0.0004107305,0.0003205646],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009285405,0.00005147639,0.9818003,0.0000184258,0.00007167142,0.0001357265,0.006752468,0.0002002196,0.0002637098,0.0004311107,0.001642469,0.008539599],"study_design_scores_gemma":[0.000004861102,0.00003187543,0.9757568,0.0000212763,0.00003155901,0.00003062274,0.02097723,0.001263778,0.00007399049,0.00008682615,0.00169761,0.0000236681],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966973,0.0001116107,0.0001394819,0.0003256728,0.00000670559,0.00003548638,0.000612746,0.000007023425,0.00206406],"genre_scores_gemma":[0.9981792,0.00009710908,0.00016207,0.00003650934,0.000003742491,0.00001408022,0.0003464835,0.00000383568,0.001157124],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0301435,"threshold_uncertainty_score":0.08899623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08908178661383069,"score_gpt":0.4155849418818076,"score_spread":0.3265031552679769,"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."}}