{"id":"W4293077668","doi":"10.1155/2022/7125472","title":"RBSmix: A Regulatable Privacy‐Preserving Method for Cryptocurrency","year":2022,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China; Ministry of Natural Resources","keywords":"Cryptocurrency; Computer science; Computer security; Database transaction; Scheme (mathematics); Anonymity; Communication source; Encryption; Voting; Blockchain; Internet privacy; Computer network; Database","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001053897,0.0001378926,0.0002171314,0.000147082,0.0026352,0.0001112613,0.003464211,0.00005580182,0.000008269169],"category_scores_gemma":[0.00002389183,0.0001573583,0.00006648838,0.0006209824,0.0000943971,0.0001406986,0.007248634,0.0003835123,0.000001002588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005262466,"about_ca_system_score_gemma":0.00006576828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006476411,"about_ca_topic_score_gemma":0.000006422679,"domain_scores_codex":[0.9985742,0.0002098217,0.0003377336,0.0004438417,0.0001322273,0.0003021866],"domain_scores_gemma":[0.996233,0.000613731,0.0001937797,0.002785532,0.0001120705,0.00006185038],"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":[0.000001921449,0.0001788268,0.0001810089,0.00002456577,0.00001844341,2.502352e-7,0.001689295,0.0005626242,0.0005927651,0.5427073,0.0005840084,0.453459],"study_design_scores_gemma":[0.0002564203,0.00007104645,0.00008944974,0.00001128335,0.000007178601,0.00002412873,0.0003183941,0.822521,0.0001449704,0.01913488,0.1572565,0.0001648125],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02589275,0.002690153,0.9675674,0.002199472,0.00007904472,0.0008373209,0.00001611486,0.0003747331,0.0003429721],"genre_scores_gemma":[0.5922607,0.00009139799,0.4064449,0.0001083289,0.00001263042,0.00101602,0.00001834945,0.000009645008,0.00003803299],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8219584,"threshold_uncertainty_score":0.9986632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02366044551783585,"score_gpt":0.3080931018080541,"score_spread":0.2844326562902182,"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."}}