{"id":"W4238740452","doi":"10.1109/msec.2019.2936696","title":"Table of contents","year":2019,"lang":"en","type":"article","venue":"IEEE Security & Privacy","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Regional Municipality of Niagara","funders":"","keywords":"Computer science; Information retrieval","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":[0.0007541112,0.0001342972,0.0002716638,0.00009174378,0.0002356493,0.00006859382,0.0009701286,0.0001688896,0.0006973248],"category_scores_gemma":[0.0006452128,0.0001416414,0.00009844791,0.0003857861,0.0001872681,0.0007093099,0.0002488253,0.0002362444,0.0004459567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007078499,"about_ca_system_score_gemma":0.0001627685,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00943559,"about_ca_topic_score_gemma":0.0007925491,"domain_scores_codex":[0.9982015,0.0002071993,0.0003013666,0.0003249037,0.000547187,0.0004178509],"domain_scores_gemma":[0.9986913,0.00009371352,0.0001861708,0.0006889217,0.0001950674,0.000144803],"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":[0.000902662,0.003670288,0.2470892,0.001225355,0.0005238989,0.00004016174,0.236483,0.0000199129,0.08441556,0.230222,0.1696418,0.02576613],"study_design_scores_gemma":[0.002062585,0.0002549916,0.00637161,0.0001429577,0.00004748619,0.000003533422,0.003731503,0.0001579664,0.03978166,0.1070386,0.8397601,0.0006470465],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9607616,0.0003143105,0.0002085052,0.001142609,0.001728137,0.0007312794,0.00005712135,0.0001320049,0.03492444],"genre_scores_gemma":[0.9984252,0.0002370629,0.0001484807,0.0001640356,0.0002727043,0.00001228688,0.00001359803,0.0000132804,0.0007133517],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6701182,"threshold_uncertainty_score":0.9971607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03044429020811235,"score_gpt":0.3011725520140281,"score_spread":0.2707282618059157,"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."}}