{"id":"W6986431964","doi":"","title":"PERBANDINGAN METODE ILLINOIS DAN METODE CANADIAN DALAM MENGHITUNG CADANGAN PREMI PADA STUDI KASUS ASURANSI JIWA BERJANGKA JOINT LIFE","year":2021,"lang":"id","type":"dissertation","venue":"Digital Repository Universitas Negeri Medan (Universitas Negeri Medan)","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Joint (building)","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":[0.0009210882,0.0005096282,0.0003913609,0.001250033,0.002896866,0.003434152,0.0007106199,0.0006141965,0.02151355],"category_scores_gemma":[0.0009282596,0.0002517905,0.0004587506,0.002052793,0.000821056,0.0006702876,0.001374251,0.0009593748,0.002462169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008462971,"about_ca_system_score_gemma":0.01702438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4289234,"about_ca_topic_score_gemma":0.7895989,"domain_scores_codex":[0.9990155,0.0001153858,0.00002852972,0.0001359512,0.000405073,0.0002995687],"domain_scores_gemma":[0.9990714,0.0000968889,0.00008593825,0.00005456403,0.0004697395,0.0002214857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001850412,0.001147304,0.2680473,0.003147993,0.0003455645,0.001596698,0.02030443,0.001815617,0.05809136,0.03003757,0.04966491,0.5639509],"study_design_scores_gemma":[0.00005542902,0.0007698468,0.4328928,0.0009833578,0.0002617832,0.0003984295,0.02903213,0.000406191,0.01292712,0.001398971,0.5207512,0.00012266],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6508539,0.01118363,0.004494428,0.005495844,0.0003760632,0.0006163814,0.005025582,0.0002105864,0.3217436],"genre_scores_gemma":[0.693203,0.01137058,0.007624222,0.001278067,0.00006210151,0.000537236,0.003330226,0.00008178589,0.2825127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4289234,"threshold_uncertainty_score":0.8528537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01483193265226501,"score_gpt":0.212967489207704,"score_spread":0.198135556555439,"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."}}