{"id":"W2296619938","doi":"10.3390/risks4010006","title":"Analysis of Insurance Claim Settlement Process with Markovian Arrival Processes","year":2016,"lang":"en","type":"article","venue":"Risks","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Markov process; Joint probability distribution; Markovian arrival process; Flexibility (engineering); Poisson process; Process (computing); Settlement (finance); Poisson distribution; Compound Poisson process; Actuarial science; Econometrics; Computer science; Operations research; Business; Economics; Mathematics; Statistics; Finance","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":[0.001499067,0.0001427163,0.0004461162,0.0003488864,0.00009823381,0.0000520984,0.0007250076,0.00006488619,0.0003525312],"category_scores_gemma":[0.001057056,0.00006361317,0.0001115739,0.002653958,0.0002589293,0.0003793834,0.00006292389,0.00006788879,0.00003672652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002799543,"about_ca_system_score_gemma":0.0002282242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004603428,"about_ca_topic_score_gemma":0.0006867979,"domain_scores_codex":[0.9971792,0.0001206312,0.0005806399,0.0005413384,0.001327836,0.0002503762],"domain_scores_gemma":[0.9973634,0.0006749349,0.0003742357,0.0006950724,0.0007864395,0.000105862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001898558,0.0001365039,0.9480394,0.00003716227,0.0002429626,0.000002628769,0.0008341999,0.00208476,0.00011721,0.0002392045,0.0001470798,0.047929],"study_design_scores_gemma":[0.001053214,0.0003068037,0.9351467,0.0001435891,0.0004005419,0.000003218048,0.0005770275,0.001514557,0.01057199,0.04699585,0.002868648,0.0004177911],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.970998,0.0001365154,0.02581972,0.0009468702,0.0000401602,0.0002014979,0.0002646863,0.00003045832,0.001562073],"genre_scores_gemma":[0.9988914,0.0000540082,0.0005203111,0.00005804049,0.00002167786,0.00002587327,0.000002937318,0.00000689558,0.0004189025],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04751121,"threshold_uncertainty_score":0.3859969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1308499208143906,"score_gpt":0.4077381097662288,"score_spread":0.2768881889518381,"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."}}