{"id":"W4296715742","doi":"10.21203/rs.3.rs-2082385/v1","title":"Measuring income inequality via percentile relativities","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Index (typography); Percentile; Inequality; Viewpoints; Economics; Econometrics; Income distribution; Economic inequality; Mathematics; Mathematical economics; Population; Distribution (mathematics); Statistics; Computer science; Sociology; Demography; Mathematical analysis","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":[0.00258273,0.0006423662,0.0006262968,0.004680012,0.0008239158,0.003772394,0.0006029509,0.0007099157,0.007991906],"category_scores_gemma":[0.02199162,0.000322593,0.0004452165,0.005794228,0.001903331,0.004614362,0.003141803,0.001425546,0.0008815823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008483681,"about_ca_system_score_gemma":0.0005839791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002638255,"about_ca_topic_score_gemma":0.001837611,"domain_scores_codex":[0.9976278,0.0009940354,0.00009317242,0.000429336,0.0006510494,0.0002047112],"domain_scores_gemma":[0.9940079,0.00344775,0.000775859,0.001055815,0.0004859146,0.0002266522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002062133,0.000125891,0.07441124,0.0001591643,0.000145019,0.00007823122,0.001536833,0.01711177,0.002999573,0.7229248,0.006389874,0.1739114],"study_design_scores_gemma":[0.00001625337,0.0001132189,0.08823132,0.0001080886,0.00008039914,0.0001840132,0.002285226,0.0739224,0.004639135,0.815549,0.01479264,0.00007828902],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4806191,0.001782257,0.3905416,0.002172924,0.0004337021,0.00009599009,0.00404766,0.001390007,0.1189169],"genre_scores_gemma":[0.9628377,0.000523757,0.03271054,0.00006313322,0.0002034738,0.00006158305,0.0007802704,0.0001409848,0.002678435],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007991906,"threshold_uncertainty_score":0.0267356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2134019988504893,"score_gpt":0.4417300095237351,"score_spread":0.2283280106732458,"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."}}