{"id":"W3035907269","doi":"10.1111/cag.12634","title":"Is it time to start worrying more about growing regional inequalities in Canada?","year":2020,"lang":"en","type":"article","venue":"Canadian Geographies / Géographies canadiennes","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Moncton","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Inequality; Divergence (linguistics); Spatial inequality; Regional science; Government (linguistics); Geography; European union; Order (exchange); Economic geography; Development economics; Political science; Economics; International trade; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003808582,0.0003997438,0.0008544392,0.002531051,0.007359386,0.0066132,0.001604042,0.001580987,0.007063631],"category_scores_gemma":[0.01962838,0.0002185279,0.0009985175,0.008184387,0.0047119,0.004742021,0.002095853,0.006070711,0.0005164519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04549721,"about_ca_system_score_gemma":0.0724164,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9898812,"about_ca_topic_score_gemma":0.99565,"domain_scores_codex":[0.9975708,0.0003192963,0.0001052317,0.0003734176,0.001004634,0.0006265473],"domain_scores_gemma":[0.9868825,0.00302509,0.001179427,0.0008219699,0.005979596,0.002111497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002186831,0.00004296321,0.2373909,0.0008468995,0.0005502778,0.0007393094,0.01525859,0.003194638,0.001043679,0.08704384,0.356529,0.2971413],"study_design_scores_gemma":[0.00003168706,0.00004802194,0.350625,0.0021115,0.0002722663,0.0003601793,0.04692538,0.003510825,0.001288098,0.05533643,0.5391,0.0003906772],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.09608205,0.0360893,0.006407842,0.8282169,0.002762648,0.00003810151,0.008959947,0.0002363545,0.02120685],"genre_scores_gemma":[0.7856617,0.05664356,0.0266891,0.1050821,0.002550163,0.00009059127,0.00551931,0.0005055217,0.01725813],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04549721,"threshold_uncertainty_score":0.3301069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03746271637571966,"score_gpt":0.1945939333442553,"score_spread":0.1571312169685356,"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."}}