{"id":"W4391912836","doi":"10.1016/j.ssmph.2024.101637","title":"Associations between gentrification, census tract-level socioeconomic status, and cycling infrastructure expansions in Montreal, Canada","year":2024,"lang":"en","type":"article","venue":"SSM - Population Health","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of Saskatchewan; Université de Sherbrooke; Université de Montréal","funders":"Canadian Institutes of Health Research","keywords":"Gentrification; Census tract; Socioeconomic status; Census; Geography; Cycling; American Community Survey; Socioeconomics; Demography; Regional science; Demographic economics; Sociology; Economic growth; Population; Economics; Archaeology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007571233,0.0005167267,0.0003979543,0.001703854,0.002863069,0.001524431,0.001865141,0.0004160862,0.006333329],"category_scores_gemma":[0.002457141,0.0003479419,0.0009289409,0.003109966,0.0011493,0.0006787605,0.00178845,0.0008922316,0.0003424248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03978413,"about_ca_system_score_gemma":0.04031266,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9979157,"about_ca_topic_score_gemma":0.9989555,"domain_scores_codex":[0.9989942,0.00008724939,0.00004057527,0.0002122439,0.0002350047,0.0004307289],"domain_scores_gemma":[0.9977902,0.00009221733,0.0003278389,0.00007688515,0.0009297122,0.0007831307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005557504,0.00002968905,0.9863647,0.00005551953,0.0001212913,0.00007620246,0.0008795622,0.0005037526,0.0001754612,0.0005336911,0.00520913,0.005995509],"study_design_scores_gemma":[0.00000517313,0.0000126091,0.9964993,0.00005248338,0.000028683,0.00001904849,0.0008677669,0.0005099968,0.00004324376,0.00004398305,0.001899126,0.00001855525],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9688761,0.002091052,0.0005882112,0.00176133,0.00006622067,0.00009818499,0.01812207,0.00008623477,0.008310623],"genre_scores_gemma":[0.9939762,0.0004336891,0.0002374173,0.0001210701,0.00001066651,0.00003149895,0.00294305,0.00001486077,0.002231568],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03978413,"threshold_uncertainty_score":0.2886554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03954140086385365,"score_gpt":0.3428245392417692,"score_spread":0.3032831383779155,"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."}}