{"id":"W1965850875","doi":"10.1002/asmb.492","title":"A risk model driven by Lévy processes","year":2003,"lang":"en","type":"article","venue":"Applied Stochastic Models in Business and Industry","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Concordia University; Society of Actuaries","keywords":"Aggregate (composite); Econometrics; Asset (computer security); Mathematical economics; Economics; Lévy process; Relevance (law); Risk model; Function (biology); Risk premium; Process (computing); Systematic risk; Computer science; Mathematics; Applied mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00150335,0.0003256789,0.0005266797,0.0002361896,0.0002803353,0.0002173625,0.0005419009,0.0006359266,0.00005235601],"category_scores_gemma":[0.001490111,0.0002488381,0.00003667248,0.001483453,0.0003095501,0.000548748,0.0001528967,0.0008311343,0.00001547215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004729999,"about_ca_system_score_gemma":0.0004134634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008877216,"about_ca_topic_score_gemma":0.00005903148,"domain_scores_codex":[0.9967816,0.00008274765,0.000775053,0.0009759784,0.0008770343,0.0005076005],"domain_scores_gemma":[0.9979761,0.0005618943,0.0002690553,0.0006206033,0.0003719068,0.000200504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004246743,0.0001609107,0.0003850232,0.00002027136,0.000007494616,0.000001207166,0.0005715678,0.9385463,0.00005353735,0.05539305,0.0006615839,0.004156608],"study_design_scores_gemma":[0.0006752076,0.000009597254,0.0001486681,0.00002833784,0.00001329225,0.000005240282,0.0002803598,0.4915012,0.00003387425,0.5069582,0.00008503594,0.0002609155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3193491,0.0003514615,0.6746324,0.0001789865,0.00006304849,0.0003595511,0.00005770224,0.00003556757,0.004972158],"genre_scores_gemma":[0.9962054,0.00009482294,0.002965551,0.0001755378,0.00002767112,0.0001507137,0.000005397454,0.00002458781,0.0003503365],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6768563,"threshold_uncertainty_score":0.9999964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07276023631530036,"score_gpt":0.3058078205499822,"score_spread":0.2330475842346819,"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."}}