{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001584529,0.000191454,0.0002133691,0.000127861,0.0001291666,0.0001088086,0.001477118,0.0004764081,0.00000654139],"category_scores_gemma":[0.00001773043,0.0001925637,0.00008453679,0.0003239556,0.0000513717,0.00009983766,0.002790924,0.0007696079,0.00002319371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008557688,"about_ca_system_score_gemma":0.0001962546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005741468,"about_ca_topic_score_gemma":0.00000359157,"domain_scores_codex":[0.9985294,0.00002224693,0.0002734979,0.0007870269,0.0001859246,0.0002018961],"domain_scores_gemma":[0.9984875,0.0000170547,0.0001440425,0.001188272,0.00008636307,0.00007674314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001668246,0.00009649236,0.00007682896,0.0000650507,0.0000387198,0.000003923605,0.0003770035,0.04844052,0.001354946,0.9414236,0.002011133,0.0061101],"study_design_scores_gemma":[0.00004805691,0.000006914561,0.00004877973,0.000009634887,0.00000780941,0.000005882287,0.000004053264,0.7686674,0.0007910786,0.2298942,0.000387442,0.0001287479],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008747677,0.00008016674,0.9811784,0.004298698,0.0001818175,0.0003435419,0.00001575138,0.00145472,0.003699211],"genre_scores_gemma":[0.5035476,0.00002232216,0.4958445,0.0004010841,0.00005061862,0.00005358315,0.000008884927,0.000009457493,0.00006194144],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7202269,"threshold_uncertainty_score":0.785252,"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."}}