{"id":"W2735839729","doi":"","title":"Comparative analysis of evaluation models in insurance solvency","year":2017,"lang":"ro","type":"article","venue":"Economie teoretică şi aplicată","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Solvency; Reinsurance; Solvency ratio; Directive; Actuarial science; European union; Business; European commission; Economics; Finance; International trade; Computer science; Market liquidity","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002583243,0.0004544545,0.002305998,0.001316704,0.0004150059,0.0002727336,0.001207575,0.0003066394,0.0008860087],"category_scores_gemma":[0.0002307779,0.0006108455,0.0006183137,0.0006511539,0.0005763273,0.001070013,0.0003369324,0.000342817,0.0004847862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005538469,"about_ca_system_score_gemma":0.0001037232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001362477,"about_ca_topic_score_gemma":0.00264613,"domain_scores_codex":[0.9957008,0.00006628317,0.002196463,0.001244368,0.0001277571,0.0006643448],"domain_scores_gemma":[0.994042,0.0001498282,0.003075128,0.002437784,0.0001714002,0.0001238371],"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":[0.0001171257,0.0004952434,0.3134587,0.00007278216,0.001125235,0.000003985639,0.003468026,0.0328453,0.000004955514,0.6366436,0.0002806868,0.01148432],"study_design_scores_gemma":[0.001118382,0.00006961232,0.6046219,0.00004885071,0.0002839215,2.146425e-7,0.000143002,0.2628938,0.00008277872,0.1293603,0.0009274777,0.0004498156],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7768613,0.003973311,0.001954944,0.0004902059,0.0006083974,0.001054376,0.001091879,0.00001542239,0.2139502],"genre_scores_gemma":[0.9963839,0.00250452,0.0003161635,0.00006696744,0.0001187014,0.0001999673,0.00008378929,0.00003170108,0.0002942894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5072834,"threshold_uncertainty_score":0.9996343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06568489603230587,"score_gpt":0.2977957651149848,"score_spread":0.2321108690826789,"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."}}