{"id":"W2962098779","doi":"10.3390/jrfm12030115","title":"Contagion Effect in Cryptocurrency Market","year":2019,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundação para a Ciência e a Tecnologia; Fundação de Amparo à Pesquisa do Estado da Bahia","keywords":"Cryptocurrency; Crash; Econometrics; Economics; Financial economics; Monetary economics; Computer science; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006445249,0.00006220936,0.0001513321,0.0001976612,0.00003326308,0.00002219858,0.0002933054,0.00004802555,0.000006481454],"category_scores_gemma":[0.00001931106,0.00005042944,0.00003790158,0.000228056,0.0000165482,0.0001087206,0.000124803,0.0001944472,0.000006235894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001808192,"about_ca_system_score_gemma":0.000008410641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007243759,"about_ca_topic_score_gemma":0.000006183738,"domain_scores_codex":[0.9994363,0.00004159304,0.0002060228,0.0001139162,0.0000983681,0.0001038438],"domain_scores_gemma":[0.9995909,0.00004773179,0.0001474919,0.0001669928,0.00002276694,0.00002415261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00002992493,0.00006321302,0.0701581,0.0000279949,0.00000471087,0.00002789399,0.0001469993,0.000005443632,0.000006054761,0.16045,0.000906637,0.768173],"study_design_scores_gemma":[0.002165182,0.0005652074,0.787689,0.000103396,0.00002004728,0.00002185381,0.0000336501,0.002491603,0.00007734926,0.1180728,0.08858618,0.0001737857],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7567317,0.0007584649,0.2399196,0.0002553005,0.000318928,0.0002475365,6.781229e-7,0.00001455358,0.001753211],"genre_scores_gemma":[0.9944425,0.000997223,0.00444974,0.00005177571,0.00002108827,0.000005217784,6.899831e-8,0.000001672751,0.000030686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7679993,"threshold_uncertainty_score":0.2056453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002305310686735457,"score_gpt":0.1972157035437902,"score_spread":0.1949103928570547,"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."}}