{"id":"W4410033711","doi":"10.1007/978-3-031-87499-4_20","title":"Privacy Guard: Empowering Users with Privacy Labels and Intuitive Apps","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Mount Royal University","funders":"","keywords":"Computer science; Guard (computer science); Internet privacy; Computer security; Privacy software; Privacy protection; Information privacy; World Wide Web","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":[0.002351654,0.001031383,0.0004250483,0.0007505256,0.001313108,0.006867953,0.001526683,0.002610618,0.01771127],"category_scores_gemma":[0.008082494,0.0006713741,0.0006541961,0.0006050512,0.003762267,0.01493683,0.006441425,0.005035684,0.006649564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005469433,"about_ca_system_score_gemma":0.0009359916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00057603,"about_ca_topic_score_gemma":0.0006532394,"domain_scores_codex":[0.998296,0.0006193812,0.00007498097,0.0002159484,0.0006108879,0.0001829285],"domain_scores_gemma":[0.9963315,0.002126408,0.0001547854,0.0008612745,0.0003154558,0.000210623],"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":[0.0002359253,0.0001286209,0.000759985,0.0003635958,0.00001783982,0.0004393504,0.00904749,0.001080343,0.00648544,0.69376,0.07226082,0.2154206],"study_design_scores_gemma":[0.00003758177,0.00009106075,0.0005074603,0.0004390849,0.0000500567,0.00133106,0.002077706,0.01275353,0.01496553,0.3846246,0.5830246,0.00009773306],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.0217684,0.003450812,0.721315,0.01091488,0.001225531,0.0002119747,0.0005793924,0.0106957,0.2298384],"genre_scores_gemma":[0.419158,0.006251847,0.2678205,0.006149265,0.0007337304,0.0006119327,0.001158179,0.00393222,0.2941843],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01771127,"threshold_uncertainty_score":0.05925012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01823125448949195,"score_gpt":0.2877171088929916,"score_spread":0.2694858544034996,"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."}}