{"id":"W1983576710","doi":"10.1177/1548512912464532","title":"Visual Analytics for cyber security and intelligence","year":2014,"lang":"en","type":"article","venue":"The Journal of Defense Modeling and Simulation Applications Methodology Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Visual analytics; Computer science; Visualization; Intelligence analysis; Data science; Context (archaeology); Set (abstract data type); Analytics; Information visualization; Information overload; State (computer science); Computer security; World Wide Web; Artificial intelligence","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":[0.00271492,0.00009146843,0.0002212595,0.0003208331,0.000212869,0.00003517752,0.0003595461,0.0001293922,8.243784e-7],"category_scores_gemma":[0.0007583071,0.00006790155,0.0000337717,0.0003943204,0.000149942,0.0001153826,0.0001244137,0.0001783229,8.749212e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001013823,"about_ca_system_score_gemma":0.00002473025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001370743,"about_ca_topic_score_gemma":0.000002020752,"domain_scores_codex":[0.9989415,0.000256882,0.000434931,0.0001539314,0.00008870084,0.0001240294],"domain_scores_gemma":[0.9973834,0.001595147,0.0002939243,0.0002774669,0.0004024407,0.00004759315],"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":[0.00001917577,0.00003532517,0.0001259091,0.00001303007,0.00003488222,1.247889e-7,0.0004363988,0.4236558,0.0001850594,0.4990052,0.00001511932,0.07647404],"study_design_scores_gemma":[0.0001192159,0.00007233847,0.00000381994,0.000004235033,0.0000418108,0.00004274794,0.0001502843,0.7471726,0.0001297134,0.2506639,0.001546352,0.00005294244],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01462337,0.0002394591,0.9826356,0.002259531,0.00004383162,0.0001344107,0.000001454308,0.00004250289,0.00001984893],"genre_scores_gemma":[0.7488989,0.0001678028,0.2506338,0.0002383119,0.00004181772,0.000004911253,0.000001318806,0.000005005949,0.000008103814],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7342755,"threshold_uncertainty_score":0.2768945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09619512117421646,"score_gpt":0.3999956883332149,"score_spread":0.3038005671589984,"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."}}