{"id":"W4210579821","doi":"10.46300/9103.2021.9.18","title":"A Complex Network Clustering and Phase Transition Models for Stock Price Dynamics before Crashes","year":2021,"lang":"en","type":"article","venue":"International Journal of Economics and Statistics","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Crash; Econometrics; Computer science; Stock market; Cluster analysis; Stock (firearms); Stock price; Stock market crash; Empirical research; Economics; Artificial intelligence; Mathematics; Engineering; Statistics; Geography; Series (stratigraphy)","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":[0.001010809,0.0005934898,0.000617308,0.001606012,0.0006557329,0.001073422,0.001301474,0.001205326,0.003938255],"category_scores_gemma":[0.004918905,0.0003537983,0.001113123,0.0008639605,0.0009412688,0.001803003,0.0009539838,0.001235913,0.0005431621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00102158,"about_ca_system_score_gemma":0.0005575375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01309719,"about_ca_topic_score_gemma":0.007733774,"domain_scores_codex":[0.9997608,0.00009376355,0.000008696577,0.00007709021,0.00002455108,0.00003503207],"domain_scores_gemma":[0.9982243,0.001046074,0.0002781063,0.0001108613,0.0001903569,0.0001502678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001319942,0.00009830826,0.00605485,0.0001086117,0.0001273308,0.0002041845,0.0003457426,0.8420285,0.001302119,0.1329813,0.003750072,0.01286713],"study_design_scores_gemma":[0.000004477861,0.000008956427,0.0005426397,0.000004404031,0.000009983806,0.00001382341,0.00001797152,0.985736,0.00004133298,0.01331461,0.0002990307,0.000006901876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2825474,0.001311719,0.7061766,0.00194736,0.0001274664,0.000148279,0.001095582,0.0004725958,0.006172888],"genre_scores_gemma":[0.9573861,0.000942047,0.03262102,0.0001196951,0.000112637,0.0001832789,0.0007405796,0.00009483441,0.007799814],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01309719,"threshold_uncertainty_score":0.02604192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04323199315094423,"score_gpt":0.2615583509531844,"score_spread":0.2183263578022402,"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."}}