{"id":"W4410787618","doi":"10.1007/978-3-031-91524-6_8","title":"AI Security and Privacy","year":2025,"lang":"en","type":"book-chapter","venue":"Progress in IS","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada; McGill University; MacEwan University; York University; University of Toronto","funders":"","keywords":"Internet privacy; Computer security; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007353808,0.0008740949,0.0005535394,0.001206287,0.001805595,0.007020942,0.0007718583,0.002230183,0.03137002],"category_scores_gemma":[0.002110586,0.0004363856,0.0003495502,0.001823976,0.006484112,0.007242007,0.001530663,0.004998593,0.01168036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003058574,"about_ca_system_score_gemma":0.001491163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002629206,"about_ca_topic_score_gemma":0.00232399,"domain_scores_codex":[0.9992197,0.0002169516,0.00002302634,0.0001226814,0.0003591597,0.000058566],"domain_scores_gemma":[0.9993429,0.0003624167,0.00002836849,0.0001426933,0.00008980349,0.00003384402],"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":[0.00000402361,0.00000745255,0.00001361097,0.00004568625,0.00000201012,0.000008504993,0.0001938375,0.0001569825,0.00008691598,0.9273617,0.04956585,0.02255337],"study_design_scores_gemma":[0.000001806408,0.000004601945,0.00004019541,0.00008132349,0.000002002544,0.00003891899,0.0000855544,0.0004658222,0.0001453142,0.5123886,0.4867415,0.000004251625],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0006055442,0.02472872,0.01959899,0.008353272,0.001366101,0.00002527912,0.0001123598,0.0001802283,0.9450296],"genre_scores_gemma":[0.06087726,0.0378807,0.01478535,0.004608456,0.00249518,0.0001223409,0.0003456889,0.0003136213,0.8785715],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.03137002,"threshold_uncertainty_score":0.1049432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02262362841600539,"score_gpt":0.2924284212463371,"score_spread":0.2698047928303317,"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."}}