{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005296157,0.001281854,0.00178666,0.001851743,0.000878761,0.002437027,0.002688194,0.002114368,0.005475638],"category_scores_gemma":[0.01395422,0.001064355,0.002010754,0.001261313,0.001541726,0.003311346,0.001511095,0.002604436,0.0006039913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002824506,"about_ca_system_score_gemma":0.002487557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0140114,"about_ca_topic_score_gemma":0.005252218,"domain_scores_codex":[0.9977534,0.0006042015,0.0001118862,0.0004062403,0.0005770856,0.0005471235],"domain_scores_gemma":[0.9894775,0.006884111,0.001756273,0.0003174993,0.001122719,0.0004419657],"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":[0.0001335741,0.00009594993,0.004255286,0.0001062017,0.00008837054,0.0005778646,0.0004219565,0.7710699,0.00201236,0.2145518,0.001043399,0.005643317],"study_design_scores_gemma":[0.00001034435,0.00001654746,0.0003613059,0.000008234823,0.00001602819,0.00004333292,0.00002748092,0.985644,0.0001130551,0.01354842,0.0001970242,0.00001426842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1596995,0.001480866,0.829149,0.001480249,0.0001171442,0.000163417,0.0003518241,0.0002769391,0.007281148],"genre_scores_gemma":[0.9672188,0.001297435,0.02134665,0.0001309374,0.0001810998,0.0001799344,0.0002736155,0.00006701369,0.009304441],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0140114,"threshold_uncertainty_score":0.02800906,"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."}}