{"id":"W1991411253","doi":"10.1111/1468-0440.00080","title":"A Model for the Detection of Insurance Fraud","year":2000,"lang":"en","type":"article","venue":"The Geneva Papers on Risk and Insurance Issues and Practice","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":86,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal; Université de Montréal","funders":"","keywords":"Computer science; Point (geometry); Insurance fraud; Actuarial science; Business; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001228991,0.0001681932,0.0002882784,0.00004261122,0.0005702692,0.00006638164,0.000182316,0.00006332222,0.00002444317],"category_scores_gemma":[0.0002765231,0.0001160463,0.00008401459,0.000158156,0.0001598132,0.000268794,0.0000225727,0.0001875388,0.00002814559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001181282,"about_ca_system_score_gemma":0.000006796932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001090494,"about_ca_topic_score_gemma":0.0001207212,"domain_scores_codex":[0.9989486,0.00005052249,0.0003928629,0.0003185383,0.00006498005,0.0002244997],"domain_scores_gemma":[0.9986353,0.000583234,0.0003493642,0.0003568804,0.00004240161,0.00003279821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002546136,0.0001610163,0.01584411,0.00009762979,0.0001925674,9.287731e-7,0.006355836,0.009636661,0.0001903046,0.03621778,0.0004015396,0.9283555],"study_design_scores_gemma":[0.001042423,0.0003027973,0.1767192,0.00002808096,0.00004772581,0.000006850482,0.0004391971,0.03374239,0.0001239703,0.01133755,0.7759222,0.0002875473],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8865348,0.07862301,0.002947694,0.004684034,0.0003059357,0.001003386,0.0004516646,0.00003298622,0.02541652],"genre_scores_gemma":[0.8181685,0.1793025,0.0002987474,0.0008437751,0.0001044334,0.00006835162,0.000001268849,0.00001562044,0.001196877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9280679,"threshold_uncertainty_score":0.4732232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02982938740449597,"score_gpt":0.2549298521078282,"score_spread":0.2251004647033322,"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."}}