{"id":"W1970155616","doi":"10.1016/j.insmatheco.2011.05.005","title":"Analysis of risk models using a level crossing technique","year":2011,"lang":"en","type":"article","venue":"Insurance Mathematics and Economics","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ruin theory; First-hitting-time model; Risk model; Renewal theory; Distribution (mathematics); Portfolio; Mathematics; Level crossing; Process (computing); Construct (python library); Probability distribution; Econometrics; Computer science; Applied mathematics; Statistics; Economics; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004131177,0.0009159527,0.001685633,0.001647333,0.0008447189,0.002492457,0.001463154,0.001469137,0.005501721],"category_scores_gemma":[0.009660882,0.0008303298,0.002700334,0.001129035,0.001166298,0.002971754,0.001653985,0.003356786,0.0005052557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001517368,"about_ca_system_score_gemma":0.00145855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002607886,"about_ca_topic_score_gemma":0.001307697,"domain_scores_codex":[0.9986563,0.0007813766,0.00004095218,0.0001184277,0.000268735,0.0001342083],"domain_scores_gemma":[0.9953966,0.003335009,0.0003644726,0.0002647478,0.0003437766,0.0002953847],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003005169,0.00006529957,0.000467223,0.00005588001,0.0001089408,0.0001107656,0.00008772299,0.3923159,0.00113142,0.5959685,0.001117143,0.008541178],"study_design_scores_gemma":[0.000003800768,0.000013165,0.00006794254,0.000006545324,0.00001262661,0.00002075635,0.00000635847,0.9193267,0.0001161173,0.08010786,0.0003113356,0.00000681466],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02215501,0.000366893,0.9725446,0.0003356947,0.00004231498,0.00002248875,0.00004812819,0.000117953,0.004367065],"genre_scores_gemma":[0.7582331,0.001091095,0.2273489,0.0002181788,0.0002096041,0.000149432,0.0002342875,0.0003046597,0.01221074],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005501721,"threshold_uncertainty_score":0.02184802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3506953146806367,"score_gpt":0.352960602962911,"score_spread":0.002265288282274291,"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."}}