{"id":"W2344495764","doi":"","title":"Assessing Financial System Vulnerabilities: An Early Warning Approach","year":2013,"lang":"en","type":"article","venue":"Bank of Canada review","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Internet privacy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.007308498,0.00178476,0.001021531,0.01281109,0.0009530985,0.002775573,0.001575196,0.001853624,0.002311435],"category_scores_gemma":[0.02128544,0.0006108164,0.0006373294,0.003854329,0.001663025,0.003898865,0.001922462,0.002610395,0.0003112443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004590877,"about_ca_system_score_gemma":0.007607187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03731503,"about_ca_topic_score_gemma":0.05749222,"domain_scores_codex":[0.997401,0.0009873111,0.0001324515,0.0001904191,0.001160614,0.0001282302],"domain_scores_gemma":[0.9911395,0.004558821,0.001437687,0.0003579633,0.002303601,0.0002023926],"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":[0.00008748932,0.0001661721,0.03821895,0.00208566,0.0006817071,0.0003681633,0.001070607,0.1590233,0.002509333,0.3692725,0.0217903,0.4047258],"study_design_scores_gemma":[0.00005021166,0.0002142089,0.02350843,0.001958926,0.0004156681,0.0006069432,0.002094341,0.3302007,0.003075083,0.5719181,0.06571231,0.000245077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01855956,0.01262852,0.9284377,0.01201165,0.0002908999,0.0004064529,0.001102597,0.0007068736,0.02585581],"genre_scores_gemma":[0.5698736,0.01964367,0.401067,0.001314776,0.0003291986,0.0003560779,0.0006232839,0.00007568781,0.006716654],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03731503,"threshold_uncertainty_score":0.07419568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02767011867383714,"score_gpt":0.2499533284072484,"score_spread":0.2222832097334112,"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."}}