{"id":"W4414692181","doi":"10.54254/2754-1169/2025.gl27550","title":"Bayesian Methods in Risk Assessment and Insurance Pricing: Strengths, Limitations, and Future Trends","year":2025,"lang":"en","type":"article","venue":"Advances in Economics Management and Political Sciences","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Bayesian probability; Scope (computer science); Risk assessment; Solvency; Process (computing); Model risk; Bayesian inference; Risk management","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04697691,0.001408418,0.00214284,0.004589838,0.0008742095,0.007093442,0.004307213,0.004249965,0.003684883],"category_scores_gemma":[0.07401048,0.001061203,0.00156813,0.006107606,0.005135792,0.0114763,0.003302864,0.00870405,0.001122743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004037696,"about_ca_system_score_gemma":0.005420984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01138049,"about_ca_topic_score_gemma":0.009220467,"domain_scores_codex":[0.9767488,0.01612954,0.0009345848,0.001427977,0.004499842,0.000259338],"domain_scores_gemma":[0.9108173,0.07620139,0.002375495,0.002736914,0.007022239,0.000846713],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000076226,0.0001001347,0.003866029,0.002651508,0.000347098,0.00008036618,0.0007431428,0.0178216,0.0002003563,0.5157829,0.007030492,0.4513001],"study_design_scores_gemma":[0.00004001762,0.000112861,0.002033117,0.006555271,0.0001410758,0.0001944006,0.0008178172,0.05564445,0.0003258091,0.8224064,0.1115906,0.0001382361],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00514653,0.4795809,0.438394,0.05721845,0.001189335,0.0001205677,0.0001859012,0.000142423,0.01802188],"genre_scores_gemma":[0.1990471,0.5183975,0.2632463,0.00837009,0.006376412,0.0005135342,0.0002246713,0.0001803828,0.003644141],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.04697691,"threshold_uncertainty_score":0.2484406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01600994972162727,"score_gpt":0.3872422902940404,"score_spread":0.3712323405724132,"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."}}