{"id":"W3134821470","doi":"10.3390/jrfm14030091","title":"Recent Developments in Cryptocurrency Markets: Co-Movements, Spillovers and Forecasting","year":2021,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Cryptocurrency; Speculation; Economics; Financial economics; Monetary economics; Business; Computer science; Finance; Computer security","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001259691,0.0002905664,0.0004092429,0.001491273,0.0005305629,0.003224649,0.0004320693,0.001545588,0.00369479],"category_scores_gemma":[0.0067515,0.000226835,0.0002379105,0.004559872,0.0009687486,0.005745616,0.0008706545,0.001749424,0.000479326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007963348,"about_ca_system_score_gemma":0.0004740499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002951896,"about_ca_topic_score_gemma":0.002655983,"domain_scores_codex":[0.999714,0.00005891745,0.00002439864,0.0000811976,0.00008524697,0.00003620924],"domain_scores_gemma":[0.9953064,0.002149093,0.001145508,0.0003053163,0.0008326693,0.0002608898],"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":[0.0004581861,0.0002387243,0.05309683,0.0009267309,0.0001747694,0.001287285,0.001300213,0.03465199,0.002588148,0.4117542,0.02621533,0.4673076],"study_design_scores_gemma":[0.0000558511,0.0002374538,0.10623,0.001029502,0.0001926715,0.001868324,0.002810908,0.1641794,0.003332687,0.4509481,0.2689261,0.0001890295],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5286349,0.2479733,0.04779344,0.08242265,0.002267648,0.00005674031,0.001340846,0.0002721854,0.08923835],"genre_scores_gemma":[0.9296805,0.05832851,0.004336253,0.0008426034,0.002715712,0.00001015557,0.0003029057,0.00002516744,0.003758176],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00369479,"threshold_uncertainty_score":0.01236033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01974678288740575,"score_gpt":0.2177507848471452,"score_spread":0.1980040019597394,"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."}}