{"id":"W2046112127","doi":"10.1109/msp.2012.123","title":"Privacy: Front and Center","year":2012,"lang":"en","type":"article","venue":"IEEE Security & Privacy","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of Ontario","funders":"","keywords":"Internet privacy; Privacy law; Information privacy; Privacy policy; Business; Personally identifiable information; Government (linguistics); Commission; Officer; Computer security; Political science; Computer science; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001273823,0.0002348903,0.0002646973,0.0001137284,0.0008190541,0.0002109159,0.0007990371,0.0002411899,0.0003754041],"category_scores_gemma":[0.0008359252,0.0002395022,0.00009737027,0.0001897846,0.0003357827,0.001669935,0.0005712362,0.0003973411,0.0003662515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001670777,"about_ca_system_score_gemma":0.000105152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002804661,"about_ca_topic_score_gemma":0.0005927799,"domain_scores_codex":[0.9974905,0.0003702811,0.0003035141,0.0004025132,0.0005359756,0.0008972366],"domain_scores_gemma":[0.9984546,0.0001008389,0.0001352355,0.0006986143,0.00008751308,0.0005232015],"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":[0.0002433617,0.002402815,0.2514259,0.0002732839,0.0002115936,0.00002236638,0.474514,3.448027e-7,0.001665204,0.04450028,0.1727655,0.05197532],"study_design_scores_gemma":[0.0007548268,0.00004938648,0.01426155,0.00003690922,0.00003331088,0.00001120003,0.001230957,0.00002009105,0.001317477,0.02822329,0.9536117,0.0004492437],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9687539,0.002093978,0.0009250481,0.005289924,0.002823748,0.0008432257,0.00006924522,0.0003811856,0.01881979],"genre_scores_gemma":[0.9956598,0.0008757452,0.0006505062,0.0005368418,0.001960509,0.00003385842,0.0000215723,0.00002493647,0.0002362351],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7808462,"threshold_uncertainty_score":0.9766615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02997790897844795,"score_gpt":0.3053867629363096,"score_spread":0.2754088539578617,"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."}}