{"id":"W3196760428","doi":"10.1017/s1748499522000057","title":"<tt>SPLICE:</tt>a synthetic paid loss and incurred cost experience simulator","year":2022,"lang":"en","type":"article","venue":"Annals of Actuarial Science","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Payment; Computer science; splice; Econometrics; Quarter (Canadian coin); Duration (music); Sequence (biology); Operations research; Economics; Engineering","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":[0.001659551,0.000518886,0.0003761826,0.0004525886,0.0002140391,0.0009587438,0.001905065,0.001018531,0.01505134],"category_scores_gemma":[0.006604103,0.0003332928,0.00071283,0.0003181697,0.0005052708,0.0007996305,0.001127161,0.001124768,0.001811958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008943843,"about_ca_system_score_gemma":0.001216948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007149359,"about_ca_topic_score_gemma":0.0050158,"domain_scores_codex":[0.9993674,0.0002186244,0.00004184051,0.00007616007,0.0002096503,0.00008630396],"domain_scores_gemma":[0.9959675,0.002211329,0.0001755004,0.0007756102,0.0006109205,0.0002590902],"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":[0.0002941445,0.0001327053,0.00437915,0.0000563555,0.00004279041,0.0001677152,0.00009494944,0.9613862,0.001115608,0.01343699,0.007274626,0.01161876],"study_design_scores_gemma":[0.00004498766,0.0000513098,0.0003694006,0.000008063775,0.00000611223,0.00003364687,0.00001617006,0.9902797,0.00115685,0.003407406,0.004616617,0.00000959105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2976388,0.0001657117,0.6216181,0.001217701,0.0004317283,0.0008297952,0.01474661,0.01727891,0.04607273],"genre_scores_gemma":[0.8654679,0.0001044037,0.1138552,0.0002479707,0.0000424501,0.0006072616,0.007676322,0.001294659,0.01070383],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01505134,"threshold_uncertainty_score":0.05035174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2661887420918283,"score_gpt":0.4639164525537511,"score_spread":0.1977277104619228,"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."}}