{"id":"W4205612339","doi":"10.1109/msec.2021.3078205","title":"Table of Contents","year":2021,"lang":"en","type":"article","venue":"IEEE Security & Privacy","topic":"Machine Learning and ELM","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Regional Municipality of Niagara","funders":"","keywords":"Table (database); Information retrieval; Computer science; Natural language processing; Database","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":[0.00015895,0.0000827183,0.0001671826,0.0000337946,0.00006073297,0.00005945752,0.0006540435,0.0000424571,0.00005420436],"category_scores_gemma":[0.0001503152,0.00008219349,0.0000621911,0.0003056536,0.00002298764,0.0002071988,0.0002623274,0.000128579,0.00006283168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000892769,"about_ca_system_score_gemma":0.00007073609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001520447,"about_ca_topic_score_gemma":0.00001082017,"domain_scores_codex":[0.9990634,0.00008132152,0.0001745511,0.0002571876,0.0002204253,0.0002031037],"domain_scores_gemma":[0.99902,0.00005223759,0.00007501131,0.0006445041,0.0001369294,0.00007133916],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007414333,0.00409314,0.07721725,0.0009165189,0.000529589,0.0009885737,0.04978945,0.0009161809,0.1106137,0.3075626,0.1572796,0.2900192],"study_design_scores_gemma":[0.00250861,0.0002306804,0.01696703,0.0001961011,0.00002959634,0.0001412206,0.0001093074,0.05631129,0.3698971,0.05263369,0.5001943,0.0007810188],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9045366,0.0006733371,0.07501162,0.003303659,0.001155421,0.00009176532,0.00000539673,0.0002076678,0.01501452],"genre_scores_gemma":[0.9943914,0.00002243011,0.004290581,0.0003129988,0.0000541166,0.000001905171,0.000002237483,0.000005191851,0.0009191789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3429147,"threshold_uncertainty_score":0.3351753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01715861963009706,"score_gpt":0.262534334037944,"score_spread":0.2453757144078469,"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."}}