{"id":"W3166248462","doi":"","title":"THE INFLUENCE OF COVID-19 PANDEMIC ON CROATIAN LIFE INSURANCE MARKET","year":2021,"lang":"en","type":"article","venue":"","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pandemic; Life insurance; Quarter (Canadian coin); Coronavirus disease 2019 (COVID-19); Actuarial science; Panel data; Economics; Coronavirus; Business; General insurance; Social insurance; Demographic economics; Insurance policy; Econometrics; Geography; Infectious disease (medical specialty); Disease; Medicine","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":[0.001205227,0.0001472716,0.0003321955,0.0007561172,0.000415987,0.002149339,0.000300678,0.0004921394,0.004624013],"category_scores_gemma":[0.002829085,0.0001214244,0.0004331347,0.0005369275,0.000483557,0.0007601963,0.0006620302,0.001234706,0.0003595391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001305063,"about_ca_system_score_gemma":0.001355049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03842768,"about_ca_topic_score_gemma":0.0302999,"domain_scores_codex":[0.9994982,0.0001079951,0.00002519244,0.00008194593,0.00009558675,0.0001911105],"domain_scores_gemma":[0.9975561,0.0007275103,0.0009806354,0.00007051261,0.0002530119,0.000412221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003090005,0.0004116356,0.9704949,0.0000605912,0.0001009045,0.0008253533,0.000251139,0.006871296,0.0005946498,0.006092696,0.004150422,0.00983738],"study_design_scores_gemma":[0.00003022126,0.0001382017,0.9767833,0.00005670189,0.00004798722,0.0001164743,0.001143592,0.01703386,0.0003757323,0.0009468264,0.003305988,0.00002116797],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99378,0.0004481199,0.0001611037,0.001048528,0.00003199187,0.00001551871,0.0005000645,0.000006364914,0.004008411],"genre_scores_gemma":[0.9982462,0.0002036905,0.00005042377,0.00006409358,0.00002538302,0.00000387809,0.000444099,0.00000222489,0.0009599384],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03842768,"threshold_uncertainty_score":0.07640803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05661912668493924,"score_gpt":0.2813891795416642,"score_spread":0.224770052856725,"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."}}