{"id":"W2728503385","doi":"10.7202/1050578ar","title":"The Transit-Oriented Development Model in Montreal (Canada): Mobilizing a Concept and Negotiating Urban Development at the Local and Metropolitan Scale","year":2017,"lang":"en","type":"article","venue":"Environnement urbain","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Institut National de la Recherche Scientifique","funders":"","keywords":"Metropolitan area; Negotiation; Regional science; Scale (ratio); Transit (satellite); Urban planning; Economic geography; Geography; Political science; Transport engineering; Sociology; Environmental planning; Economic growth; Public transport; Engineering; Civil engineering; Social science; Cartography; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001055156,0.0004434934,0.0001888012,0.001059015,0.0136594,0.007387711,0.001428873,0.0009784503,0.005737695],"category_scores_gemma":[0.001638035,0.0002068766,0.0002647488,0.002254603,0.01000335,0.002502909,0.002950833,0.001680673,0.0002306048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1107423,"about_ca_system_score_gemma":0.1110441,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9913248,"about_ca_topic_score_gemma":0.9964033,"domain_scores_codex":[0.9987078,0.0004259399,0.00002088872,0.0001295746,0.0002598576,0.0004560271],"domain_scores_gemma":[0.9993766,0.0001023412,0.00003879028,0.00003221825,0.0001986087,0.0002514952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004221293,0.00004687193,0.007443557,0.00009285113,0.00001493785,0.0007911321,0.0367947,0.004758595,0.0007874536,0.9004456,0.01941107,0.02937095],"study_design_scores_gemma":[0.0000558229,0.00009834593,0.02443016,0.0003625517,0.0000509818,0.0003843813,0.1152164,0.01017077,0.001002559,0.06905804,0.7789642,0.0002058173],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2764922,0.004062453,0.02125735,0.05126553,0.000346042,0.0003296789,0.00109634,0.0002409326,0.6449094],"genre_scores_gemma":[0.9444327,0.001475546,0.005258812,0.0007231212,0.00001756195,0.00008231016,0.000125154,0.00003731114,0.04784757],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1107423,"threshold_uncertainty_score":0.8034952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0113903327694083,"score_gpt":0.2401229958778122,"score_spread":0.228732663108404,"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."}}