{"id":"W3107937663","doi":"10.3390/jrfm13120301","title":"Early Warning Signs of Financial Market Turmoils","year":2020,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Ecosystem dynamics and resilience","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Stylized fact; Volatility clustering; Volatility (finance); Econometrics; Stock market; Predictive power; Financial market; Economics; Warning system; Financial economics; Market data; Market timing; Cluster analysis; Contrast (vision); Computer science; Finance; Autoregressive conditional heteroskedasticity; Artificial intelligence; Geography; Macroeconomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001179721,0.0004325199,0.0004182192,0.001677551,0.0002205496,0.001494612,0.0004480325,0.0008588118,0.001577874],"category_scores_gemma":[0.009032854,0.0002330647,0.0003074041,0.0004395166,0.0004964027,0.001448057,0.0006615036,0.0008832832,0.0002522671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003883822,"about_ca_system_score_gemma":0.0002456284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001459115,"about_ca_topic_score_gemma":0.001655796,"domain_scores_codex":[0.9997981,0.00004816877,0.00001555013,0.00004554152,0.0000608363,0.00003186325],"domain_scores_gemma":[0.9941075,0.002698382,0.002072893,0.0003808009,0.0004054088,0.0003349891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001033608,0.0002661003,0.6545723,0.0002683513,0.0003435616,0.001127608,0.0006531798,0.2327196,0.01920579,0.02166335,0.003937929,0.06420858],"study_design_scores_gemma":[0.00001834088,0.0001479026,0.1642689,0.00004734735,0.0000287062,0.0002462481,0.0001711329,0.816802,0.005390296,0.01217895,0.0006418098,0.00005837987],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9579391,0.0003014399,0.03847161,0.0002552638,0.0000328655,0.00003626514,0.0003803026,0.000690384,0.001892712],"genre_scores_gemma":[0.9969771,0.00005409614,0.002665775,0.00001531488,0.000009562916,0.000004170297,0.0001339913,0.00000992796,0.0001301041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001677551,"threshold_uncertainty_score":0.006239057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003645874788787428,"score_gpt":0.173070586653826,"score_spread":0.1694247118650386,"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."}}