{"id":"W1950238674","doi":"10.3968/j.css.1923669720110704.z50","title":"The Researches on Calculating Method of Insurance Premium of Residential Mortgage Loan","year":2011,"lang":"en","type":"article","venue":"Canadian social science","topic":"Safety and Risk Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Actuarial science; Business; Insurance policy; Bond insurance; Auto insurance risk selection; Loan; Payment; General insurance; Mortgage insurance; Casualty insurance; Key person insurance; Stochastic game; Finance; Economics; Microeconomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002230893,0.00007211107,0.0001085338,0.000221449,0.0009467273,0.00007450558,0.000685328,0.00003325949,0.0000466955],"category_scores_gemma":[0.0004021328,0.00005512021,0.00005201425,0.001107296,0.0007177329,0.0003939928,0.0001255357,0.0001071313,0.00001237909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008071106,"about_ca_system_score_gemma":0.000181636,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1227575,"about_ca_topic_score_gemma":0.04516012,"domain_scores_codex":[0.9987077,0.00002714743,0.0002084685,0.000194855,0.0004772524,0.0003845813],"domain_scores_gemma":[0.9993332,0.00005687875,0.0001815544,0.0001920535,0.0002032526,0.00003304988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0000751515,0.000039308,0.08408599,0.0001259595,0.00002767645,0.00001525055,0.002246343,0.00002340207,0.00185125,0.840634,0.002270042,0.06860555],"study_design_scores_gemma":[0.0002729768,0.00002279254,0.9609838,0.00007527779,0.00002360575,3.193154e-7,0.004956028,0.000768205,0.002800616,0.009698448,0.0201629,0.0002350014],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2661787,0.00004465253,0.0003257926,0.0007553837,0.0004664552,0.0003700678,0.000008496168,0.00002219599,0.7318283],"genre_scores_gemma":[0.9990911,0.000004935983,0.00024834,0.0002025883,0.0002271058,0.000005044798,5.973806e-7,0.000006400921,0.0002138651],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8768978,"threshold_uncertainty_score":0.9722632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05843000947258815,"score_gpt":0.2993880532181593,"score_spread":0.2409580437455712,"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."}}