{"id":"W2895353537","doi":"10.2139/ssrn.3189051","title":"Bitcoin Microstructure and the Kimchi Premium","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Business; Microstructure; Econometrics; Monetary economics; Economics; Materials science; Metallurgy","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":[0.000680258,0.0001352579,0.0003454282,0.000534674,0.0004069909,0.002231616,0.0002533908,0.0006676643,0.005931823],"category_scores_gemma":[0.006844332,0.0001546943,0.00009324733,0.0004757432,0.0005156865,0.002510967,0.0005915536,0.0008700022,0.0003808273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005704989,"about_ca_system_score_gemma":0.0002775344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001733081,"about_ca_topic_score_gemma":0.002452279,"domain_scores_codex":[0.9998826,0.00002361851,0.000006267803,0.00002190931,0.00003161365,0.00003397872],"domain_scores_gemma":[0.9971227,0.001065957,0.0009334564,0.0002235037,0.0002520605,0.0004022633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.002901363,0.0005390219,0.3499691,0.0001952338,0.0002173559,0.003108131,0.001573348,0.02868764,0.02809294,0.5105852,0.01060925,0.06352137],"study_design_scores_gemma":[0.000171324,0.0001715021,0.4329017,0.00007931782,0.0001272922,0.0009988887,0.0009454841,0.2871574,0.004721906,0.2688808,0.003711009,0.0001333971],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897222,0.0003182649,0.001817953,0.0007949478,0.00002550701,0.000006191552,0.00006652516,0.00002431771,0.00722417],"genre_scores_gemma":[0.9991003,0.00006252507,0.00007576191,0.00001464669,0.00002591786,0.000001268547,0.00001622195,0.000004938803,0.0006984378],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005931823,"threshold_uncertainty_score":0.01984394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005942012964139389,"score_gpt":0.1940868857321337,"score_spread":0.1881448727679943,"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."}}