{"id":"W3086719973","doi":"10.14763/2020.3.1502","title":"Going global: Comparing Chinese mobile applications’ data and user privacy governance at home and abroad","year":2020,"lang":"en","type":"article","venue":"Internet Policy Review","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Internet privacy; Business; Corporate governance; Computer science; Information privacy; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000325065,0.0001345548,0.0003060316,0.00001114759,0.0001532647,0.0001274589,0.0009495458,0.00004609249,0.00007811371],"category_scores_gemma":[0.0007080595,0.0001212478,0.0000268521,0.0003575379,0.0001530815,0.0005213082,0.002256313,0.0001102875,0.0001091357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001213749,"about_ca_system_score_gemma":0.00005548156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004391488,"about_ca_topic_score_gemma":0.001145945,"domain_scores_codex":[0.9988306,0.000109498,0.0002549648,0.0004263666,0.0001683243,0.0002103172],"domain_scores_gemma":[0.9990317,0.00004219999,0.0001581219,0.0005434384,0.00002782677,0.0001967339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007267298,0.000192441,0.3670229,0.01227374,0.0002021859,0.000009811913,0.01222472,0.000001075244,0.00006914194,0.0892447,0.2508753,0.2678113],"study_design_scores_gemma":[0.0001405069,0.00001610093,0.007088333,0.0002935674,0.00003334025,0.000007803353,0.00001710913,0.0001678506,0.00000165948,0.0008126897,0.9912763,0.0001447566],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1429402,0.781096,0.00259007,0.0467142,0.0001986333,0.00539795,0.0009861118,0.0004953129,0.01958151],"genre_scores_gemma":[0.7838172,0.2112601,0.0003439714,0.00365611,0.0005031704,0.0001240616,0.00006384133,0.0000116839,0.0002198856],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.740401,"threshold_uncertainty_score":0.6638645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05701056990772162,"score_gpt":0.3941000693751139,"score_spread":0.3370894994673923,"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."}}