{"id":"W7109013785","doi":"10.3886/e210004","title":"Data and Code for: Accounting for Wealth Concentration in the United States","year":2025,"lang":"en","type":"dataset","venue":"ICPSR Data Holdings","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Earnings; Distribution (mathematics); Capital (architecture); Net worth; Net income; Relevance (law); Capital income; Comprehensive income; Income distribution; National wealth","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0007306472,0.0009069415,0.000535152,0.003252347,0.000494274,0.001306892,0.001225732,0.0008620857,0.03369813],"category_scores_gemma":[0.004623714,0.0005047695,0.0006282048,0.007318776,0.0002182446,0.0008459001,0.0011369,0.001044758,0.02873449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001109421,"about_ca_system_score_gemma":0.00169421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1130487,"about_ca_topic_score_gemma":0.117912,"domain_scores_codex":[0.99937,0.00008390855,0.0001092951,0.0001482399,0.0001910277,0.00009756871],"domain_scores_gemma":[0.9973021,0.0003615212,0.000631904,0.000488987,0.001014616,0.0002009654],"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":[0.00003745157,0.00004792935,0.01204752,0.0001786059,0.00003144336,0.00002864357,0.0000403419,0.0005772786,0.00005905484,0.0006415789,0.9820315,0.00427861],"study_design_scores_gemma":[0.0002622754,0.00003367132,0.1438309,0.0003677064,0.00004321018,0.00009808652,0.0003244604,0.001659387,0.0004706662,0.001402048,0.8514425,0.00006493438],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009639702,0.00003376196,0.00006047287,0.00006165988,0.00001338142,0.00001640183,0.9976332,0.0001088303,0.001108446],"genre_scores_gemma":[0.001955237,0.00004410894,0.0002640783,0.00004079963,0.00000833249,0.0001048997,0.9965391,0.00003106401,0.00101238],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1130487,"threshold_uncertainty_score":0.2247814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.102649234484409,"score_gpt":0.3855324841204102,"score_spread":0.2828832496360012,"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."}}