{"id":"W1920558578","doi":"10.25336/p6p31m","title":"Going Up? Canada's metropolitan areas and their role as escalators or elevators","year":2015,"lang":"en","type":"article","venue":"Canadian Studies in Population","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Demographic economics; Productivity; Economic growth; Geography; Socioeconomics; Sociology; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0005739877,0.0001942183,0.0002303477,0.001101875,0.01064411,0.00334953,0.0009728274,0.0004297507,0.004436268],"category_scores_gemma":[0.001403366,0.0001483407,0.000248029,0.002763731,0.0025132,0.001026363,0.002115984,0.001022897,0.0001857994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03856145,"about_ca_system_score_gemma":0.05754583,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9943827,"about_ca_topic_score_gemma":0.9987471,"domain_scores_codex":[0.9991723,0.000101834,0.00001431463,0.00005458251,0.0001485806,0.0005084566],"domain_scores_gemma":[0.9986083,0.00005947752,0.0001484214,0.00002804039,0.0003116105,0.000844101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001162586,0.0001054221,0.7019154,0.0002240455,0.00006107262,0.0008955823,0.1285761,0.0002528605,0.0004933237,0.05445522,0.03888477,0.07401983],"study_design_scores_gemma":[0.000007699266,0.00002962993,0.7246841,0.0004605855,0.00004863275,0.0001597831,0.209413,0.0001694886,0.0001253049,0.0008563153,0.06400863,0.00003685417],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9297226,0.004563979,0.0001569921,0.0137165,0.00011761,0.00002855673,0.0007941549,0.00001258648,0.05088698],"genre_scores_gemma":[0.9915376,0.002461265,0.0001603394,0.0004046941,0.00001657025,0.000006796515,0.0001363335,0.000006469478,0.00526998],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03856145,"threshold_uncertainty_score":0.2797842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07132423738708422,"score_gpt":0.3354853491243891,"score_spread":0.2641611117373049,"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."}}