{"id":"W4285254353","doi":"10.2139/ssrn.4119978","title":"Cryptocurrency Venues: Segmentation, Fees, and Tax Policies","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Cryptocurrency; Business; Segmentation; Tax law; Economics; Finance; Monetary economics; Double taxation; Computer science; Computer security; Artificial intelligence","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":[0.001846555,0.0001812201,0.0005307893,0.001507502,0.00185907,0.005646091,0.0008734493,0.001418457,0.02354525],"category_scores_gemma":[0.01498423,0.0002001604,0.0002112407,0.002565212,0.001443295,0.005814433,0.001485797,0.001435432,0.001178848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003771523,"about_ca_system_score_gemma":0.002666405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006054368,"about_ca_topic_score_gemma":0.01728003,"domain_scores_codex":[0.9984706,0.0005651371,0.00005194203,0.0001396528,0.0002300635,0.0005425689],"domain_scores_gemma":[0.9865003,0.006689996,0.00202779,0.0006428735,0.001030239,0.003108678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.002864026,0.000844117,0.1197133,0.0002186493,0.0001174934,0.0006607916,0.0008700671,0.05314698,0.001767214,0.6954864,0.01428015,0.1100309],"study_design_scores_gemma":[0.0002986259,0.0005634974,0.06684371,0.0002634937,0.0001396778,0.0008171168,0.006265658,0.1599897,0.004869307,0.7332675,0.02654227,0.0001395485],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8735313,0.001877557,0.01344312,0.003203441,0.00007681284,0.0001038025,0.0007609884,0.0001592662,0.1068437],"genre_scores_gemma":[0.9971879,0.00008090489,0.0001974919,0.00002426181,0.000007254878,0.00000360928,0.00005223752,0.00000862245,0.002437621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02354525,"threshold_uncertainty_score":0.07876676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005782639585442785,"score_gpt":0.2341241042391618,"score_spread":0.228341464653719,"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."}}