{"id":"W2989363982","doi":"10.69554/asww3312","title":"Personal data protection in blockchain","year":2019,"lang":"en","type":"article","venue":"Journal of data protection & privacy.","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Privacy Analytics (Canada)","funders":"","keywords":"Blockchain; Data Protection Act 1998; Computer security; Internet privacy; Computer science","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":[0.007509258,0.0002239698,0.0003947487,0.0005600851,0.0004368642,0.0002741558,0.00399112,0.000289896,0.0004910401],"category_scores_gemma":[0.003598644,0.0002162848,0.00007756552,0.0009741059,0.0001394042,0.004194179,0.002019575,0.001282513,0.0001523578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004130738,"about_ca_system_score_gemma":0.0007404453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005178077,"about_ca_topic_score_gemma":0.001860853,"domain_scores_codex":[0.9959378,0.0008462513,0.0008723135,0.0006727023,0.001191625,0.0004792671],"domain_scores_gemma":[0.9965187,0.00007780951,0.0009059739,0.002011674,0.0002877018,0.0001981923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004417822,0.003582822,0.01699931,0.0009296908,0.0006375367,0.0002170879,0.03444479,0.0001859095,0.04287324,0.002162929,0.04334927,0.8501996],"study_design_scores_gemma":[0.003930299,0.000913157,0.008102896,0.0005172369,0.00009581323,0.0003644375,0.006347487,0.01988749,0.0007854226,0.007389448,0.9508447,0.0008216],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8967015,0.001498643,0.05532974,0.02986758,0.006057058,0.00706647,0.0007243705,0.0002882632,0.002466343],"genre_scores_gemma":[0.9942577,0.0003195847,0.003068315,0.0001149105,0.001812085,0.00002686475,0.0001145112,0.00003188293,0.0002540797],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9074954,"threshold_uncertainty_score":0.8819837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1099074494383356,"score_gpt":0.3433165357891764,"score_spread":0.2334090863508408,"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."}}