{"id":"W2120552230","doi":"10.2139/ssrn.2373149","title":"How Superadditive Can a Risk Measure Be?","year":2013,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Superadditivity; Measure (data warehouse); Risk measure; Business; Computer science; Mathematics; Economics; Financial economics; Mathematical economics; Data mining","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":[0.010545,0.00194761,0.001871076,0.002674987,0.001286847,0.007931527,0.001588342,0.002793024,0.00532968],"category_scores_gemma":[0.05170309,0.0007941596,0.001482907,0.002296292,0.006794651,0.02056637,0.003533671,0.00514144,0.001064574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00213784,"about_ca_system_score_gemma":0.00122568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007221719,"about_ca_topic_score_gemma":0.0004781381,"domain_scores_codex":[0.9936093,0.002562325,0.0005482766,0.0009955236,0.001869179,0.000415363],"domain_scores_gemma":[0.9701645,0.02014124,0.003333506,0.002449526,0.002416762,0.001494462],"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":[0.00002404304,0.00004656035,0.0007952118,0.0001267984,0.00007612161,0.00006359089,0.000172166,0.004840608,0.0003002723,0.9693136,0.002421786,0.02181931],"study_design_scores_gemma":[0.00000499879,0.0000295995,0.0004415719,0.00005033797,0.00002635121,0.0001402893,0.0001009912,0.006064268,0.0002230984,0.9897764,0.003124933,0.00001727499],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.202351,0.01142154,0.5978725,0.06422479,0.00236025,0.00007058114,0.0005419856,0.0004862152,0.1206712],"genre_scores_gemma":[0.9347158,0.00383563,0.04854051,0.003174092,0.001753603,0.0001115306,0.0001890224,0.0001948964,0.00748487],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.010545,"threshold_uncertainty_score":0.05576795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02658578206667801,"score_gpt":0.2812740760837648,"score_spread":0.2546882940170868,"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."}}