{"id":"W3015191929","doi":"10.36227/techrxiv.12098067.v1","title":"Bitcoin Price Prediction using ARIMA Model","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Autoregressive integrated moving average; Liberian dollar; Currency; Cryptocurrency; Renminbi; Scalability; Value (mathematics); Focus (optics); Digital currency; Computer science; Economics; Monetary economics; Finance; Time series; World Wide Web; Exchange rate; Machine learning; Database","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":[0.001162371,0.0008051667,0.0007705578,0.001119963,0.0003763571,0.001217731,0.0009461102,0.0010058,0.004094386],"category_scores_gemma":[0.004512585,0.0003600591,0.0009738007,0.001033951,0.0002653396,0.001083533,0.0004479286,0.001699497,0.001053064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000505847,"about_ca_system_score_gemma":0.0006962685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03138361,"about_ca_topic_score_gemma":0.01623719,"domain_scores_codex":[0.9994156,0.0001212261,0.00004334765,0.000185609,0.0001349577,0.00009923815],"domain_scores_gemma":[0.9981717,0.001075208,0.0002190262,0.00009597398,0.0003722906,0.00006573783],"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":[0.0003483941,0.0002212486,0.04536897,0.0001170526,0.0001597968,0.0003235155,0.0001051314,0.8978454,0.002855999,0.003918093,0.003731304,0.04500505],"study_design_scores_gemma":[0.000004230206,0.00001461139,0.001543838,0.00000351368,0.000008148331,0.0000120028,0.000006149909,0.9974282,0.0002582108,0.0005191038,0.0001936586,0.000008298779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6978746,0.00112682,0.2854796,0.001281108,0.0003533633,0.000112992,0.00341798,0.002594344,0.007758981],"genre_scores_gemma":[0.9739257,0.0003424875,0.02004532,0.0000774488,0.00007624494,0.00005057866,0.001763617,0.00007644035,0.003642221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03138361,"threshold_uncertainty_score":0.06240189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04609419513258081,"score_gpt":0.2680920802569109,"score_spread":0.2219978851243301,"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."}}