{"id":"W7097140824","doi":"","title":"Discussion Papers in Economics and Econometrics Consumption, Income and Wealth Inequality in Canada","year":2009,"lang":"en","type":"article","venue":"","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inequality; Income inequality metrics; Economic inequality; Consumption (sociology); Income distribution; Distribution (mathematics); Offset (computer science)","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":[0.00435644,0.0004995736,0.001296054,0.003629413,0.003297172,0.005925413,0.0009413985,0.001602492,0.02057768],"category_scores_gemma":[0.01651797,0.000349322,0.0008148821,0.01305421,0.00232177,0.001305611,0.001150097,0.001720529,0.0009523128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03844863,"about_ca_system_score_gemma":0.06586681,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9793823,"about_ca_topic_score_gemma":0.9704511,"domain_scores_codex":[0.9970034,0.0007916676,0.0001650176,0.0002662961,0.001023576,0.0007501788],"domain_scores_gemma":[0.9894483,0.004591492,0.0008551653,0.0004804024,0.003850081,0.0007745501],"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":[0.0001498775,0.0001391152,0.2098305,0.0006716244,0.0006689655,0.0005393924,0.002106652,0.01434054,0.0001488876,0.19764,0.4576285,0.1161359],"study_design_scores_gemma":[0.0001301161,0.00004031777,0.3166456,0.001250328,0.0003385954,0.0001194801,0.006463523,0.01891064,0.0004039648,0.06754345,0.5879717,0.0001823213],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.2528139,0.2328222,0.015808,0.2202193,0.004452859,0.0002705757,0.04426742,0.0004014686,0.2289441],"genre_scores_gemma":[0.7833704,0.09204513,0.006240768,0.008255371,0.002126707,0.0002020973,0.0127837,0.0002571454,0.0947186],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03844863,"threshold_uncertainty_score":0.2789657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03249805402466709,"score_gpt":0.2890670702647781,"score_spread":0.256569016240111,"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."}}