{"id":"W4328054586","doi":"10.47743/saeb-2023-0013","title":"Flip the Coin: Heads, Tails or Cryptocurrencies?","year":2023,"lang":"en","type":"article","venue":"Scientific Annals of Economics and Business","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundação para a Ciência e a Tecnologia","keywords":"Cryptocurrency; Volatility (finance); Economics; Currency; Unit of account; Liberian dollar; Us dollar; Autoregressive conditional heteroskedasticity; Econometrics; Monetary economics; Financial economics; Finance; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002629357,0.000160709,0.0004004706,0.0002791662,0.0003697799,0.000362991,0.0003940962,0.00007902994,0.000363522],"category_scores_gemma":[0.0002443002,0.0001278304,0.00009954472,0.0009460784,0.0004691421,0.0002798446,0.000206835,0.00009019524,0.0001127504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001279967,"about_ca_system_score_gemma":0.00007767523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001287372,"about_ca_topic_score_gemma":0.0001767323,"domain_scores_codex":[0.9983567,0.00001512885,0.0006834417,0.0005353164,0.00003085402,0.0003785516],"domain_scores_gemma":[0.9986512,0.000126298,0.0004049901,0.000562262,0.0001655666,0.00008969606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001882743,0.0002191398,0.05536745,0.0003172267,0.0001519669,0.000004543485,0.0008784664,0.0007046285,0.00002863138,0.8535935,0.05949503,0.02905113],"study_design_scores_gemma":[0.000392073,0.00003795848,0.09422793,0.00003225893,0.000005824481,0.000004066515,0.0002109221,0.1871121,0.00004042197,0.1688583,0.5486863,0.000391931],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9851556,0.001030018,0.0001541351,0.00541851,0.001759804,0.000258907,0.0006843827,0.00002923258,0.005509384],"genre_scores_gemma":[0.9912542,0.003330218,0.00009372945,0.0002342095,0.0000993311,0.00001993567,0.00007344337,0.00001974998,0.004875182],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6847352,"threshold_uncertainty_score":0.5212771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1447570102434153,"score_gpt":0.2820527789559215,"score_spread":0.1372957687125062,"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."}}