{"id":"W2214696323","doi":"","title":"INCOME CHANGES AND DYNAMICS OF A HOUSING AFFORDABILITY GINI IN CANADA","year":2015,"lang":"en","type":"article","venue":"","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economics; Earnings; Debt; Economic inequality; Gini coefficient; Inequality; Demographic economics; Income distribution; Household debt; Household income; Income inequality metrics; Labour economics; Geography; Macroeconomics; Finance","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":[0.0006172775,0.0002169946,0.0004021295,0.001957991,0.001984166,0.001763974,0.0007049143,0.0003161797,0.003112683],"category_scores_gemma":[0.002681296,0.0001980338,0.0004540624,0.004517214,0.0008102151,0.0005018464,0.001165958,0.001036645,0.0001625852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04241539,"about_ca_system_score_gemma":0.01833865,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9961714,"about_ca_topic_score_gemma":0.9960033,"domain_scores_codex":[0.9994352,0.00002460979,0.0000127935,0.00007634617,0.0001878772,0.0002631275],"domain_scores_gemma":[0.9987251,0.00008383441,0.0001937276,0.00004901653,0.0006231031,0.0003251689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000177167,0.0000433407,0.9301673,0.00005495428,0.0001087895,0.0002501295,0.003136494,0.007681963,0.0005198094,0.01760741,0.01211141,0.0281412],"study_design_scores_gemma":[0.000004320095,0.000006885181,0.9870535,0.00001962345,0.00001144789,0.00002738395,0.0009056216,0.005133708,0.0000894406,0.0004499473,0.006281019,0.00001717874],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9747536,0.001126301,0.0005111138,0.002537283,0.0000289077,0.00002600777,0.008332115,0.00005163869,0.01263291],"genre_scores_gemma":[0.9945387,0.0003326717,0.0002454086,0.00005121653,0.00000602567,0.000004460963,0.002318388,0.00001085919,0.002492253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04241539,"threshold_uncertainty_score":0.3077466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03036377585516335,"score_gpt":0.1922768298746878,"score_spread":0.1619130540195245,"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."}}