{"id":"W3156230674","doi":"","title":"Privacy Law Issues in Public Blockchains: An Analysis of Blockchain, PIPEDA,The GDPR, and Proposals for Compliance","year":2019,"lang":"en","type":"article","venue":"Canadian journal of law and technology","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Blockchain; Compliance (psychology); Computer security; Internet privacy; Business; Privacy law; Law; Information privacy; Computer science; Political science; Privacy policy; Psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01721734,0.0004245435,0.0009914596,0.003602153,0.005732143,0.01131951,0.002392601,0.008270495,0.01134958],"category_scores_gemma":[0.04891223,0.0007637539,0.001956563,0.005102991,0.01554863,0.01582821,0.005516458,0.007452385,0.0005671124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01065275,"about_ca_system_score_gemma":0.01790923,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01706511,"about_ca_topic_score_gemma":0.01782105,"domain_scores_codex":[0.9839167,0.006255332,0.0005343623,0.0008877051,0.005600587,0.002805315],"domain_scores_gemma":[0.9475672,0.04013568,0.002153095,0.004203708,0.004886641,0.001053665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001681612,0.0000136718,0.0003714787,0.00001973408,0.000004657045,0.0000443586,0.0003650974,0.001756761,0.00004756777,0.9945663,0.000540638,0.002252996],"study_design_scores_gemma":[0.00003757195,0.0000446372,0.001039072,0.0001409786,0.00003159039,0.00008018675,0.001303253,0.01313386,0.0003619345,0.9707875,0.01301033,0.00002905285],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.3288573,0.00316907,0.1697101,0.06520279,0.0002583857,0.0009990747,0.0005881937,0.0002051439,0.4310099],"genre_scores_gemma":[0.9725447,0.0008622387,0.009718895,0.001413528,0.0001042014,0.0002977916,0.00009659926,0.00004613816,0.01491596],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9829349,"threshold_uncertainty_score":0.0910551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03886243406111548,"score_gpt":0.312785630546291,"score_spread":0.2739231964851755,"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."}}