{"id":"W4403536936","doi":"10.1145/3691620.3695353","title":"CompAi: A Tool for GDPR Completeness Checking of Privacy Policies using Artificial Intelligence","year":2024,"lang":"en","type":"article","venue":"","topic":"Digital and Cyber Forensics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds National de la Recherche Luxembourg","keywords":"Completeness (order theory); Computer science; Information privacy; Artificial intelligence; Computer security; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001553491,0.0001127191,0.0001759046,0.00009425909,0.0000636471,0.0003992395,0.000543659,0.00002838469,0.000007454716],"category_scores_gemma":[0.00002633627,0.00009249763,0.0001110779,0.0004323849,0.00009350794,0.0005147629,0.0002890298,0.00004818377,0.00001514233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002453752,"about_ca_system_score_gemma":0.0000810058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000632702,"about_ca_topic_score_gemma":0.000007000172,"domain_scores_codex":[0.9990143,0.000009193031,0.0003157227,0.0002468796,0.000180062,0.0002339059],"domain_scores_gemma":[0.9994238,0.0001334314,0.0000422403,0.0002665959,0.00009737511,0.00003653566],"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":[0.000002866649,0.00002921912,0.00002897433,0.000074448,0.00001385165,0.000001880345,0.0005177887,0.0003575464,0.001680676,0.9125077,0.0001161803,0.08466891],"study_design_scores_gemma":[0.00002199189,0.00006029905,0.00009139556,0.0001119822,0.000008494942,0.00001638247,0.00009059114,0.6644878,0.04808815,0.2830205,0.003818311,0.0001840747],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09182212,0.00006745658,0.9053852,0.0003065549,0.0003251271,0.0001478883,0.000009620008,0.0001556684,0.001780367],"genre_scores_gemma":[0.9304532,0.000001119579,0.06922022,0.0001133009,0.00007927161,0.000004990083,0.000002326389,0.000008184401,0.0001173516],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8386311,"threshold_uncertainty_score":0.3849876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1172724724525778,"score_gpt":0.3279365953983724,"score_spread":0.2106641229457946,"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."}}