{"id":"W4417448684","doi":"10.1002/for.70077","title":"When Are Statistical Forecast Gains Economically Relevant? Evidence From Bitcoin Returns","year":2025,"lang":"en","type":"article","venue":"Journal of Forecasting","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"Wilfrid Laurier University","keywords":"Bivariate analysis; Index (typography); Forecast error; Trading strategy; Consensus forecast; Stock market index; Stock market; Yield (engineering)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007958854,0.0001445609,0.0003451055,0.0002384488,0.0001707485,0.0001386736,0.001211806,0.000148627,0.0000240776],"category_scores_gemma":[0.001254996,0.0001269653,0.0001080341,0.0002823495,0.0001057595,0.0004084,0.0003158133,0.0005865943,0.000008420567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001250334,"about_ca_system_score_gemma":0.0002004142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003101716,"about_ca_topic_score_gemma":0.00008726096,"domain_scores_codex":[0.9984278,0.00007214093,0.0007576388,0.0002940536,0.0001758202,0.0002725287],"domain_scores_gemma":[0.9973434,0.001167647,0.0006745674,0.0004555115,0.000257892,0.0001010296],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001824155,0.0004312601,0.05607406,0.0001397696,0.0004307231,0.0005414157,0.003093206,0.0007692089,0.002992373,0.3153365,0.0422682,0.5777408],"study_design_scores_gemma":[0.0007751607,0.0002437878,0.01553269,0.001339851,0.00007190268,0.0002795103,0.0002729276,0.476832,0.002639096,0.4961763,0.005493041,0.0003437026],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2654409,0.0005296752,0.7254623,0.007767288,0.0002881388,0.00009442961,0.00001231706,0.00005301635,0.0003519273],"genre_scores_gemma":[0.7393249,0.00004432778,0.2602317,0.0002510257,0.00009779684,0.000004234248,7.098836e-7,0.000005697741,0.0000396214],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5773972,"threshold_uncertainty_score":0.5177494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04572255639616593,"score_gpt":0.2808088333070624,"score_spread":0.2350862769108965,"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."}}