{"id":"W2124778170","doi":"10.1111/j.1541-0064.2012.00438.x","title":"Are new patterns of low‐income distribution emerging in Canadian metropolitan areas?","year":2012,"lang":"en","type":"article","venue":"Canadian Geographies / Géographies canadiennes","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Metropolitan area; Geography; Poverty; Socioeconomics; Distribution (mathematics); Census; Population; Socioeconomic status; Disadvantaged; Demography; Economic growth; Sociology; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007419506,0.0004149129,0.000602441,0.004975734,0.001286121,0.0001010131,0.0005627399,0.0002802307,0.0003081652],"category_scores_gemma":[0.0006736098,0.0004666013,0.0003112056,0.006473861,0.001102406,0.0006582293,0.00003497341,0.0002809977,0.000009470726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001454651,"about_ca_system_score_gemma":0.001150819,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9994975,"about_ca_topic_score_gemma":0.9999932,"domain_scores_codex":[0.9953371,0.000222328,0.0006194782,0.0004364286,0.0004507551,0.002933934],"domain_scores_gemma":[0.9944978,0.0001913404,0.0003340365,0.0004403471,0.0003105842,0.004225941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005110923,0.00001755716,0.9400553,0.00003643498,0.00009890463,0.00002391713,0.00731792,0.000003987406,6.818267e-7,0.04708989,0.004222324,0.001127942],"study_design_scores_gemma":[0.0002375894,0.00002146933,0.802268,0.000127792,0.00003824939,0.000003073129,0.08918539,0.000002734714,0.000006033527,0.0007123206,0.106934,0.0004633041],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981465,0.005347514,0.00001169626,0.002899834,0.001402918,0.0004893837,0.001205367,0.00007417159,0.007104063],"genre_scores_gemma":[0.9968712,0.001612585,0.00002088155,0.0003246125,0.0004454706,0.00004356381,0.0001488598,0.00003873082,0.0004941098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1377873,"threshold_uncertainty_score":0.9997786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01382189170166791,"score_gpt":0.2403950632451837,"score_spread":0.2265731715435158,"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."}}