{"id":"W2135293140","doi":"10.1007/s11009-010-9184-9","title":"Ruin Analysis of a Threshold Strategy in a Discrete-Time Sparre Andersen Model","year":2010,"lang":"en","type":"article","venue":"Methodology And Computing In Applied Probability","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ruin theory; Mathematics; First-hitting-time model; Mathematical economics; Applied mathematics; Risk model; Dividend; Discrete time and continuous time; Statistics; Econometrics; Economics","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":[],"consensus_categories":[],"category_scores_codex":[0.02819316,0.0002352907,0.001258926,0.0006545744,0.00009869642,0.00003660982,0.000657002,0.0004053113,0.0000681676],"category_scores_gemma":[0.00191979,0.0001798713,0.0001473046,0.002121687,0.000794279,0.0000902648,0.0003908293,0.000814892,0.000003691981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002818469,"about_ca_system_score_gemma":0.0001381088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001468778,"about_ca_topic_score_gemma":0.003541681,"domain_scores_codex":[0.9953347,0.001290067,0.001369569,0.001140451,0.0004318221,0.0004334184],"domain_scores_gemma":[0.9931371,0.005374326,0.0003440878,0.0009440602,0.00009840517,0.0001019815],"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":[0.0003528547,0.0002833198,0.2032063,0.00002885813,0.00007707094,0.0000020992,0.001840263,0.6716205,0.006538871,0.09757264,0.000005206689,0.01847208],"study_design_scores_gemma":[0.0002423314,0.00002013103,0.05648207,0.000002951787,0.00003409602,9.477678e-7,0.00008462408,0.4936609,0.0001282753,0.4492431,0.000001456788,0.00009916323],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8480752,0.00003008304,0.1486634,0.0001884393,0.00004412425,0.0004245136,0.00000987456,0.00002469322,0.002539627],"genre_scores_gemma":[0.8865882,0.000002068259,0.1132997,0.00005042879,0.00001154351,0.00001505059,0.000004106048,0.000005820263,0.00002308859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3516704,"threshold_uncertainty_score":0.9771244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2510528195617971,"score_gpt":0.4254875751582296,"score_spread":0.1744347555964325,"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."}}