{"id":"W2963094141","doi":"10.1109/models.2019.00-20","title":"Using Models to Enable Compliance Checking Against the GDPR: An Experience Report","year":2019,"lang":"en","type":"article","venue":"","topic":"Model-Driven Software Engineering Techniques","field":"Computer Science","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"General Data Protection Regulation; Context (archaeology); Computer science; Process (computing); Data Protection Act 1998; Knowledge management; Process management; Computer security; Business","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":[0.0292644,0.001253274,0.0008009826,0.002428333,0.001680814,0.007424039,0.003367491,0.002664841,0.003331526],"category_scores_gemma":[0.05968427,0.001426753,0.002340663,0.002451439,0.002541488,0.01223551,0.004582337,0.004146084,0.001386626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003821179,"about_ca_system_score_gemma":0.005859217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01720621,"about_ca_topic_score_gemma":0.0163263,"domain_scores_codex":[0.9733468,0.01597096,0.001889834,0.001373364,0.006690549,0.0007285362],"domain_scores_gemma":[0.9406255,0.0345867,0.002470267,0.01517892,0.006518757,0.0006198219],"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":[0.0005032097,0.001844004,0.01752034,0.00142395,0.0002466444,0.001327838,0.02407186,0.1357071,0.01586082,0.2924604,0.02005549,0.4889783],"study_design_scores_gemma":[0.0001506176,0.0006035469,0.003273687,0.001677674,0.0002527723,0.001164304,0.00462955,0.5985256,0.03737128,0.08427307,0.2677255,0.0003524479],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06829657,0.001080827,0.9013044,0.003757542,0.0001791497,0.0007143315,0.0006412087,0.007537407,0.01648858],"genre_scores_gemma":[0.2625827,0.001269636,0.7277272,0.000455977,0.00003977049,0.0003507984,0.002111267,0.001766876,0.003695798],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0292644,"threshold_uncertainty_score":0.1547668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.143442596924163,"score_gpt":0.3274558141941102,"score_spread":0.1840132172699472,"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."}}