{"id":"W4380079374","doi":"10.32920/23467526.v1","title":"Empirical Estimation of the Haezendonck-Goovaerts Risk","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Measure (data warehouse); Risk measure; Expected shortfall; Coherent risk measure; Estimation; Spectral risk measure; Empirical measure; Portfolio optimization; Econometrics; Convergence (economics); Value at risk; Estimator; Dynamic risk measure; Computer science; Empirical research; Mathematics; Statistics; Portfolio; Mathematical optimization; Risk management; Data mining; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.006483203,0.0006448858,0.0006268409,0.001221242,0.0003134183,0.001554414,0.001298864,0.0009549696,0.002554472],"category_scores_gemma":[0.03943936,0.0002752991,0.0004034865,0.0009468957,0.00172404,0.002702133,0.001213829,0.001523294,0.0003176359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001567483,"about_ca_system_score_gemma":0.001410907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005754886,"about_ca_topic_score_gemma":0.00347811,"domain_scores_codex":[0.9978287,0.00106756,0.00009981349,0.0002823189,0.0006323061,0.00008927858],"domain_scores_gemma":[0.9876139,0.009428605,0.001070068,0.0009667624,0.0007653086,0.0001554219],"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":[0.00009559281,0.00005067932,0.01671978,0.0001693842,0.0001121963,0.0001421396,0.0002049088,0.6199657,0.001997846,0.2853822,0.001993453,0.07316606],"study_design_scores_gemma":[0.00001153555,0.00004382388,0.004871747,0.00006009674,0.00001643656,0.00008063336,0.00008324444,0.9202194,0.002734386,0.06962746,0.002218019,0.00003312707],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1500119,0.001318836,0.8369263,0.001290384,0.00005436019,0.00009083431,0.0002673381,0.0003048413,0.009735239],"genre_scores_gemma":[0.8525697,0.0009382211,0.1416254,0.0001040598,0.00005819322,0.0001119652,0.0003810166,0.0001302515,0.004081226],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006483203,"threshold_uncertainty_score":0.03428686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05781369501387726,"score_gpt":0.3377235342509617,"score_spread":0.2799098392370845,"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."}}