{"id":"W2525610626","doi":"10.7202/1069177ar","title":"PROTECTING ONLINE PRIVACY IN THE PRIVATE SECTOR: IS THERE A ‘BETTER’ MODEL?","year":2020,"lang":"en","type":"article","venue":"Revue québécoise de droit international","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Internet privacy; Privacy policy; The Internet; Cyberspace; Legislation; Business; Privacy by Design; Data Protection Act 1998; Information privacy; Privacy law; Legal aspects of computing; Inclusion (mineral); Enforcement; Personally identifiable information; Computer security; Public relations; Political science; Computer science; Law; World Wide Web; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007546402,0.0001283786,0.0001397444,0.00007889774,0.0002635021,0.0001724761,0.001386871,0.0001096287,0.00017141],"category_scores_gemma":[0.001176386,0.0001219379,0.00009568576,0.0003075814,0.00006846742,0.0003983338,0.000167445,0.0005476807,0.00004197633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000322341,"about_ca_system_score_gemma":0.0002204222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005264505,"about_ca_topic_score_gemma":0.00584897,"domain_scores_codex":[0.9984149,0.0002257041,0.0002899732,0.0003309514,0.000444346,0.0002940779],"domain_scores_gemma":[0.9992977,0.0001103087,0.0001509511,0.0002684685,0.00007705835,0.00009551897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005283582,0.00131855,0.03421979,0.0003933862,0.0002842993,0.0002493855,0.5993889,0.001877805,0.004830679,0.2961885,0.008800228,0.05192013],"study_design_scores_gemma":[0.001473217,0.0001581964,0.01119769,0.0003324373,0.00004834118,0.00004539299,0.006610492,0.2513282,0.0005895946,0.2365238,0.4908765,0.0008161931],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8729778,0.00009642409,0.009433709,0.1018637,0.0002204545,0.0008514765,0.0001444541,0.000142397,0.01426956],"genre_scores_gemma":[0.9893265,0.0001203441,0.001664892,0.007448152,0.001210856,0.00008216264,0.00004102157,0.00001813665,0.00008789323],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5927784,"threshold_uncertainty_score":0.7958393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04634030246360775,"score_gpt":0.3004203944541821,"score_spread":0.2540800919905743,"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."}}