{"id":"W4406940056","doi":"10.1016/j.physa.2025.130417","title":"Long-range correlations in cryptocurrency markets: A multi-scale DFA approach","year":2025,"lang":"en","type":"article","venue":"Physica A Statistical Mechanics and its Applications","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of the Fraser Valley","funders":"Taylor’s University","keywords":"Cryptocurrency; Range (aeronautics); Scale (ratio); Statistical physics; Econophysics; Econometrics; Mathematics; Computer science; Materials science; Physics; World Wide Web","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":[0.000186405,0.0001585494,0.0004072903,0.0002070593,0.0001911805,0.00007429381,0.0001655729,0.00006626808,0.0001764706],"category_scores_gemma":[0.00005647625,0.000180106,0.00006952633,0.0007457199,0.00002382294,0.00009917183,0.00009349945,0.0001650658,0.0001095057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005287534,"about_ca_system_score_gemma":0.00001979559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001379795,"about_ca_topic_score_gemma":0.00008423525,"domain_scores_codex":[0.9986168,0.00001993493,0.0005699531,0.0005104184,0.00004011331,0.0002427542],"domain_scores_gemma":[0.9992672,0.0001489114,0.000145411,0.0003036489,0.00004567981,0.00008910108],"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":[0.000005212706,0.0003556886,0.001156833,0.00006996436,0.00003600706,2.45517e-7,0.00007931748,0.00002309324,0.000009240094,0.9961681,0.0002613379,0.001834973],"study_design_scores_gemma":[0.0005386533,0.00002002657,0.02083968,0.00002221765,0.00003494977,8.537298e-7,0.0001069891,0.6860286,0.000001574835,0.2743003,0.01785211,0.0002540297],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0006986594,0.001318181,0.9877263,0.000351598,0.00004815172,0.0006765161,0.0009098544,0.00003096532,0.008239759],"genre_scores_gemma":[0.9832156,0.0002302832,0.01441542,0.00007557552,0.00004081073,0.0009774541,0.0001288724,0.00001766131,0.0008983026],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9825169,"threshold_uncertainty_score":0.734451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02510326663831193,"score_gpt":0.25232224661144,"score_spread":0.2272189799731281,"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."}}