{"id":"W4311782971","doi":"10.54691/bcpbm.v34i.3163","title":"Time Series Analysis and Prediction on Bitcoin","year":2022,"lang":"en","type":"article","venue":"BCP Business & Management","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Autoregressive integrated moving average; Econometrics; Cryptocurrency; Time series; Computer science; Residual; Economics; Investment (military); Currency; Asset (computer security); Machine learning; Monetary economics; Algorithm; Computer security","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":[0.001246533,0.0006665934,0.0004402311,0.002023474,0.000323513,0.0009501757,0.000375844,0.0005374536,0.002567005],"category_scores_gemma":[0.006069221,0.000142456,0.0006460429,0.002997001,0.0002006924,0.001150469,0.0003655792,0.00095155,0.0006938699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005965806,"about_ca_system_score_gemma":0.0004834111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01932072,"about_ca_topic_score_gemma":0.00775971,"domain_scores_codex":[0.9993595,0.0001370656,0.00006480877,0.0001460104,0.0002207531,0.00007179673],"domain_scores_gemma":[0.997918,0.001141145,0.0003013911,0.0001236976,0.0004410673,0.00007462592],"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":[0.0005378782,0.0005005173,0.3329538,0.0004189495,0.0003150578,0.001177481,0.00072524,0.3772866,0.006275648,0.01458938,0.01234987,0.2528696],"study_design_scores_gemma":[0.000008931177,0.000065212,0.05575089,0.00003389225,0.00003263168,0.00007409479,0.000159697,0.9380666,0.001413085,0.002470165,0.001895404,0.0000294488],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9231628,0.001099161,0.0630989,0.001172839,0.0001875677,0.00008179329,0.003793005,0.0008971793,0.006506805],"genre_scores_gemma":[0.9862216,0.00060496,0.008497516,0.00003041386,0.000050746,0.00004201462,0.002691275,0.0000360597,0.0018255],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01932072,"threshold_uncertainty_score":0.0384165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004767790978793224,"score_gpt":0.1917705500170863,"score_spread":0.1870027590382931,"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."}}