{"id":"W2744632005","doi":"","title":"Optimal Auditing for Insurance Fraud","year":2002,"lang":"en","type":"article","venue":"Cahiers de recherche","topic":"Law, Economics, and Judicial Systems","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Audit; Insurance fraud; Deterrence theory; Business; Actuarial science; Accounting; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006170287,0.0006695964,0.001910722,0.001193869,0.000800762,0.003077174,0.0009011136,0.002055111,0.008185239],"category_scores_gemma":[0.03603755,0.0008909858,0.0005364172,0.00102484,0.001552462,0.003499447,0.002083575,0.002434308,0.0006151232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003272656,"about_ca_system_score_gemma":0.005292207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00430328,"about_ca_topic_score_gemma":0.003897396,"domain_scores_codex":[0.9963812,0.001923444,0.0002179374,0.00041512,0.0005355754,0.000526686],"domain_scores_gemma":[0.989292,0.006799845,0.001221113,0.0009553044,0.001125146,0.0006066455],"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":[0.001443552,0.0004025763,0.003429782,0.0004886998,0.0001421873,0.0002135714,0.0002632671,0.4172682,0.00146464,0.3840172,0.02723834,0.1636281],"study_design_scores_gemma":[0.0002204461,0.00013158,0.0013658,0.00009654265,0.000056246,0.0000692577,0.0000881969,0.583495,0.0006240554,0.4110136,0.002815726,0.00002362497],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.24066,0.006448809,0.6542965,0.01798162,0.0008488427,0.0007206784,0.0008143988,0.001143019,0.07708606],"genre_scores_gemma":[0.9624398,0.001129207,0.02970723,0.0001947793,0.000205387,0.00007126907,0.0001092684,0.00004847524,0.006094529],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008185239,"threshold_uncertainty_score":0.03263199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1869632204713474,"score_gpt":0.2897695046686149,"score_spread":0.1028062841972675,"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."}}