{"id":"W3047104034","doi":"10.3934/bdia.2020001","title":"Modeling portfolio loss by interval distributions","year":2020,"lang":"en","type":"article","venue":"Big Data and Information Analytics","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Bank of Canada","funders":"","keywords":"Portfolio; Interval (graph theory); Outcome (game theory); Mathematics; Statistics; Econometrics; Capital allocation line; Regression analysis; Regression; Computer science; Economics; Mathematical economics; Combinatorics","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":[0.0005900677,0.00008204372,0.0001384278,0.00006847487,0.00009246398,0.0003143941,0.0005857514,0.0000464013,0.00005129305],"category_scores_gemma":[0.002340639,0.00006152078,0.00002412395,0.0004072578,0.00004211115,0.001910923,0.0003179163,0.00009241759,0.0001445175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001148899,"about_ca_system_score_gemma":0.00004704554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006744203,"about_ca_topic_score_gemma":6.918811e-7,"domain_scores_codex":[0.9987812,0.00001549991,0.0005326347,0.0001499206,0.000401099,0.0001196425],"domain_scores_gemma":[0.9991107,0.00007300024,0.00008367324,0.0004186559,0.0001491547,0.0001648263],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004169836,0.00004133707,0.0009822545,0.00004969271,0.00006702148,0.000003823045,0.0009299362,0.09435697,0.00002376044,0.03003143,0.7425995,0.1308726],"study_design_scores_gemma":[0.0001051728,0.00001312531,0.00003690462,0.000003784951,0.00001191901,0.000002950114,0.0001888531,0.81846,0.000004078614,0.0004437086,0.1806597,0.00006979999],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001919059,0.00005495927,0.9939423,0.001709035,0.000116179,0.00005398468,0.001319925,0.00003945043,0.0008450602],"genre_scores_gemma":[0.9960184,0.00009750643,0.001506843,0.0008599411,0.00007275646,9.315229e-7,0.001386558,0.000002681992,0.0000544581],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9940993,"threshold_uncertainty_score":0.303171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2173420492690235,"score_gpt":0.3329600770183434,"score_spread":0.1156180277493199,"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."}}