{"id":"W4205726858","doi":"10.1109/msp.2014.36","title":"Table of contents","year":2014,"lang":"en","type":"article","venue":"IEEE Security & Privacy","topic":"Security and Verification in Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Regional Municipality of Niagara","funders":"","keywords":"Table (database); Computer science; 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":[0.000452507,0.0001137316,0.0001997685,0.00007421117,0.000110135,0.00008040085,0.001397881,0.00006682119,0.00001845111],"category_scores_gemma":[0.000186508,0.0001182777,0.00006957003,0.0003545651,0.00005713476,0.0003700619,0.0002308915,0.0001492232,0.00006627198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001571385,"about_ca_system_score_gemma":0.0000364179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007904488,"about_ca_topic_score_gemma":0.000002929849,"domain_scores_codex":[0.9987124,0.00010403,0.0003215638,0.0003289584,0.0002844653,0.0002485363],"domain_scores_gemma":[0.9985171,0.0001681239,0.0001847048,0.0008721675,0.0001698181,0.00008811573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002245885,0.0007092063,0.007026672,0.0002287099,0.0000796129,0.000005326115,0.0152393,0.0002005442,0.01577082,0.8990832,0.01570258,0.04593159],"study_design_scores_gemma":[0.001897338,0.0002892592,0.006733532,0.0001757439,0.00001974824,0.00003244757,0.00008009686,0.3475874,0.2497782,0.1584362,0.2341645,0.0008056258],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3376107,0.0001156494,0.6538201,0.0008609291,0.00123794,0.0001571923,0.000002689512,0.0002196189,0.00597522],"genre_scores_gemma":[0.9906736,0.00001054496,0.008766979,0.0003670806,0.0001236505,0.000004275691,0.000001480414,0.000006462862,0.00004594923],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.740647,"threshold_uncertainty_score":0.4823223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02654297890321161,"score_gpt":0.2627548521789878,"score_spread":0.2362118732757762,"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."}}