{"id":"W3122041687","doi":"","title":"Chartbook of economic inequality","year":2014,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Sustainable Development and Environmental Policy","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inequality; Geography; Earnings; Download; Population; Development economics; Economy; Economics; Demography; Sociology","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":[0.001592687,0.0016072,0.001008733,0.01220789,0.001013332,0.005392534,0.001274639,0.0008748131,0.1163176],"category_scores_gemma":[0.01151275,0.0005016169,0.0006733557,0.02544953,0.0005832204,0.004208606,0.001671355,0.00273536,0.03896844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002496043,"about_ca_system_score_gemma":0.00377574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03125971,"about_ca_topic_score_gemma":0.01571329,"domain_scores_codex":[0.9983526,0.0001980648,0.0001425941,0.0001741387,0.0009904245,0.000142145],"domain_scores_gemma":[0.9928799,0.001845242,0.0005985793,0.0007916403,0.00350763,0.0003770572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002169761,0.00001112083,0.00034602,0.0002349178,0.000006891144,0.00001585225,0.00004053334,0.0005932275,0.00003844151,0.02073656,0.9171665,0.0607881],"study_design_scores_gemma":[0.000006076075,0.000008814977,0.002455453,0.0002606281,0.000003711108,0.00004067139,0.00003553483,0.0001869577,0.00005635474,0.005894393,0.9910347,0.00001667058],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"dataset","genre_scores_codex":[0.002651,0.03530049,0.01540025,0.0074804,0.009710289,0.0005468082,0.4575188,0.004273317,0.4671186],"genre_scores_gemma":[0.03445832,0.06917855,0.03050491,0.002438113,0.004690966,0.001993946,0.5087547,0.004576613,0.3434039],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.1163176,"threshold_uncertainty_score":0.3891211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02605159202131846,"score_gpt":0.300099675445336,"score_spread":0.2740480834240175,"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."}}