{"id":"W4224316621","doi":"10.1145/3485447.3512223","title":"Et tu, Brute? Privacy Analysis of Government Websites and Mobile Apps","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ACM Web Conference 2022","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Android (operating system); Internet privacy; BitTorrent tracker; Password; World Wide Web; Computer security; The Internet; Computer science; Government (linguistics)","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":[0.001646784,0.0002279848,0.0003102879,0.002590652,0.0009197087,0.002587365,0.0003332893,0.000676078,0.001669989],"category_scores_gemma":[0.01641446,0.0002139406,0.0005649409,0.003039009,0.0008096051,0.002568363,0.0008936892,0.0007432303,0.000718422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008081017,"about_ca_system_score_gemma":0.0006694391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009037687,"about_ca_topic_score_gemma":0.005793376,"domain_scores_codex":[0.996857,0.0009049333,0.0002422812,0.000513616,0.001085204,0.0003968499],"domain_scores_gemma":[0.9857711,0.006576687,0.002688466,0.002504813,0.002157737,0.000301211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000623546,0.0002230198,0.8501518,0.0002755716,0.0001641806,0.0008800363,0.003606638,0.004069927,0.003522321,0.01341454,0.006889957,0.1161786],"study_design_scores_gemma":[0.0000186001,0.0002052183,0.9008506,0.000144046,0.0001177232,0.002957321,0.005557545,0.04399171,0.008287805,0.009898937,0.02789638,0.00007420553],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9786453,0.0007571595,0.003472857,0.0004396184,0.0000215605,0.00005134895,0.002558319,0.0002072282,0.01384654],"genre_scores_gemma":[0.9950784,0.000197964,0.001516397,0.0000847447,0.00001455202,0.00003131621,0.001562248,0.00003317815,0.001481156],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009037687,"threshold_uncertainty_score":0.01797014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02479004339928924,"score_gpt":0.2849386553110434,"score_spread":0.2601486119117541,"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."}}