{"id":"W4242534416","doi":"10.32920/ryerson.14662176","title":"Rearrangement Algorithm in Risk Aggregation","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Risk measure; Measure (data warehouse); Aggregate (composite); Discretization; Expected shortfall; Exponential function; Econometrics; Portfolio; Actuarial science; Investment (military); Coherent risk measure; Economics; Mathematics; Spectral risk measure; Computer science; Financial 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":[0.002401828,0.0006440746,0.001058811,0.0009083429,0.000555674,0.001569755,0.001339403,0.001174375,0.006151552],"category_scores_gemma":[0.01063125,0.0004204822,0.000848607,0.001191283,0.001334072,0.002389036,0.002099904,0.001731173,0.001181707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001301161,"about_ca_system_score_gemma":0.001060072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003346693,"about_ca_topic_score_gemma":0.002148964,"domain_scores_codex":[0.9987502,0.0006162819,0.00007325829,0.0001837273,0.0002615788,0.0001150201],"domain_scores_gemma":[0.9973603,0.00162756,0.0002012695,0.0004062558,0.0003124835,0.00009207997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002241515,0.00007305227,0.0008952723,0.00009395208,0.00006118035,0.0001469919,0.0002542861,0.5174484,0.003489163,0.3168145,0.003745237,0.1567539],"study_design_scores_gemma":[0.00002624339,0.00004234122,0.0001066667,0.00001379536,0.000009235759,0.00003397265,0.0000284429,0.9047943,0.001140803,0.09099083,0.002801189,0.00001213605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007776256,0.0001498858,0.9891801,0.0002235048,0.0000381774,0.00003963156,0.00002507087,0.0002378338,0.002329561],"genre_scores_gemma":[0.3343996,0.0003896681,0.6554223,0.0003018964,0.0001352697,0.0003411802,0.0002151992,0.0003347806,0.008460183],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006151552,"threshold_uncertainty_score":0.02057898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07475718654506924,"score_gpt":0.3766298443416548,"score_spread":0.3018726577965856,"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."}}