{"id":"W2123060712","doi":"10.1007/11424918_20","title":"Privacy Compliance Enforcement in Email","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"University of Guelph","keywords":"Computer science; Enforcement; Compliance (psychology); Computer security; Internet privacy; Information privacy; World Wide Web; Law; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009212429,0.0004797786,0.0007889445,0.001582368,0.003174536,0.006023496,0.001912355,0.003892225,0.008536651],"category_scores_gemma":[0.03073637,0.0006387378,0.0007657132,0.001702022,0.002281707,0.008648012,0.004295944,0.003593708,0.002406559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001418436,"about_ca_system_score_gemma":0.001894709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001130337,"about_ca_topic_score_gemma":0.0008493253,"domain_scores_codex":[0.9874572,0.006264119,0.000972978,0.001152441,0.003034143,0.001118998],"domain_scores_gemma":[0.9736277,0.01536726,0.001734033,0.006851535,0.002026831,0.0003926526],"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":[0.0004704334,0.0004272065,0.003651158,0.0002191186,0.00004311827,0.0007630693,0.002736742,0.01349305,0.003741617,0.6251741,0.02161063,0.3276698],"study_design_scores_gemma":[0.00007854523,0.0001617103,0.002099234,0.0003844319,0.0001062737,0.001231643,0.001433365,0.1742226,0.02026084,0.7159658,0.08397441,0.00008100267],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07836593,0.001747369,0.7680457,0.007634777,0.0005427409,0.0003280473,0.0002662853,0.004415486,0.1386536],"genre_scores_gemma":[0.8514186,0.0006292132,0.103797,0.0012836,0.0003065988,0.0002287061,0.0003726936,0.0003587949,0.04160484],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009212429,"threshold_uncertainty_score":0.0487206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04806259338967786,"score_gpt":0.3144971398352871,"score_spread":0.2664345464456093,"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."}}