{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01032944,0.0001528691,0.0002696623,0.0002634203,0.0009984792,0.0005403203,0.001383736,0.00005995793,0.00000426324],"category_scores_gemma":[0.001146134,0.0001046338,0.00004610958,0.0004102335,0.0009094979,0.001386131,0.0003875059,0.0002381227,0.000004575445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001521696,"about_ca_system_score_gemma":0.0003610588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001320948,"about_ca_topic_score_gemma":0.0001952991,"domain_scores_codex":[0.9979067,0.0000222715,0.0006916235,0.0003422524,0.0005359747,0.0005011563],"domain_scores_gemma":[0.9982431,0.0006530379,0.0002667333,0.0003944148,0.0003571276,0.00008558542],"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":[0.00003226107,0.0001020542,0.0002665949,0.0004798926,0.00002206818,4.826015e-7,0.005990885,0.005221958,0.000002047806,0.9830883,0.001822063,0.002971423],"study_design_scores_gemma":[0.0005016295,0.00006155451,0.0007115335,0.0001379879,0.000003669775,0.000006870502,0.0002315765,0.5586594,0.000002417496,0.4345697,0.005018884,0.00009470621],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1887412,0.002034989,0.7887819,0.01484276,0.000448852,0.002607415,0.001343625,0.00003018263,0.001169109],"genre_scores_gemma":[0.8925484,0.001895346,0.1036359,0.001095269,0.0003172483,0.0002559547,0.0001895488,0.00001851574,0.00004389351],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7038072,"threshold_uncertainty_score":0.7679595,"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."}}