{"id":"W7161991940","doi":"10.82308/51364","title":"The urban and regional dimensions of economic inequality in Canada, 1996 - 2006","year":2010,"lang":"en","type":"dissertation","venue":"","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inequality; Microdata (statistics); Socioeconomic status; Earnings; Census; Economic inequality; Spatial inequality; Population","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"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":[0.0007576116,0.0002869249,0.0003460202,0.003470513,0.004664097,0.002145634,0.0008593668,0.0002507341,0.002692833],"category_scores_gemma":[0.002585829,0.0002068666,0.0003563713,0.01143878,0.0008802057,0.0004869245,0.001361686,0.0007857329,0.0002558056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.08472773,"about_ca_system_score_gemma":0.06940889,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.998758,"about_ca_topic_score_gemma":0.9994154,"domain_scores_codex":[0.9990097,0.00003302273,0.00003914682,0.0001024783,0.0004683668,0.0003472033],"domain_scores_gemma":[0.9980679,0.00005819207,0.0002028352,0.00003773742,0.00125898,0.0003742567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001805128,0.00007677993,0.8154093,0.0003096662,0.0001209716,0.0001890414,0.01032992,0.001652468,0.0002550202,0.006543695,0.05235927,0.1125735],"study_design_scores_gemma":[0.000002574347,0.000004248648,0.9863688,0.00005954503,0.00001300837,0.00001635308,0.002544149,0.0002381863,0.0000461148,0.00009162464,0.01060607,0.000009267732],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8556941,0.01298811,0.0004642915,0.00842631,0.0001478724,0.0001447212,0.06567195,0.00007027893,0.05639233],"genre_scores_gemma":[0.966433,0.00635008,0.0006730546,0.0002636828,0.00004575976,0.0000390536,0.01281221,0.00001680661,0.01336631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08472773,"threshold_uncertainty_score":0.6147456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02383047094805923,"score_gpt":0.2915842006668806,"score_spread":0.2677537297188213,"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."}}