{"id":"W2478318209","doi":"","title":"Strong laws for generalized absolute Lorenz curves when data are stationary and ergodic sequences","year":2004,"lang":"en","type":"article","venue":"Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Centrum Wiskunde and Informatica; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; European Research Consortium for Informatics and Mathematics","keywords":"Mathematics; Ergodic theory; Lorenz curve; Absolute continuity; Absolute (philosophy); Stationary ergodic process; Mathematical analysis; Invariant measure; Inequality","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":[0.006938671,0.001093433,0.001563021,0.004416967,0.001070474,0.003803638,0.001661241,0.001899339,0.004315505],"category_scores_gemma":[0.04785164,0.000838001,0.001504487,0.001901381,0.004817021,0.00874973,0.003338581,0.002690779,0.0006950907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001620766,"about_ca_system_score_gemma":0.0008766251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001356911,"about_ca_topic_score_gemma":0.0007948565,"domain_scores_codex":[0.9971119,0.00100826,0.0001949485,0.0006885792,0.0006467951,0.0003495563],"domain_scores_gemma":[0.9740892,0.01587435,0.004284837,0.002267986,0.002368161,0.001115426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004294475,0.00001908159,0.001719976,0.0001112878,0.00004054226,0.0002723903,0.0004872313,0.03116876,0.001834222,0.9537202,0.0008343374,0.009748993],"study_design_scores_gemma":[0.00002657784,0.00007942778,0.001818345,0.00008071144,0.00002168153,0.0004060957,0.0001536768,0.2685816,0.000929939,0.7248665,0.002971632,0.00006389467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1422795,0.00125816,0.8402345,0.001575963,0.00009054169,0.000155269,0.0003624805,0.0003995325,0.01364407],"genre_scores_gemma":[0.9211235,0.00218953,0.06705566,0.000521531,0.0005006616,0.0004517414,0.0004068053,0.0002081951,0.007542532],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006938671,"threshold_uncertainty_score":0.0366956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2658905966081549,"score_gpt":0.3740503321510646,"score_spread":0.1081597355429098,"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."}}