{"id":"W4386883447","doi":"10.1109/icmcis59922.2023.10253516","title":"Enabling Activity Based Intelligence with Visual Analytics","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Visual analytics; Computer science; Data science; Analytics; Intelligence analysis; Visualization; Domain (mathematical analysis); Currency; Data visualization; Social network analysis; Graph; Big data; Business intelligence; World Wide Web; Artificial intelligence; Knowledge management; Data mining; Social media; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001372531,0.0009681097,0.0005230169,0.00376093,0.0004916759,0.0051869,0.001257338,0.0007192512,0.007264393],"category_scores_gemma":[0.004953466,0.0004519517,0.0008875757,0.002195505,0.0009084187,0.003854232,0.006354769,0.001614515,0.001790562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006449537,"about_ca_system_score_gemma":0.0007337774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002871516,"about_ca_topic_score_gemma":0.003241628,"domain_scores_codex":[0.9992643,0.0001973826,0.00004381427,0.0001195623,0.0002889614,0.0000859505],"domain_scores_gemma":[0.9981745,0.0009429503,0.0001226825,0.0003510687,0.0002591325,0.0001495349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007698703,0.0002375212,0.005847781,0.001085905,0.0001884552,0.000811037,0.005694787,0.07523893,0.04033818,0.2948449,0.06870239,0.5062402],"study_design_scores_gemma":[0.000123069,0.0001060853,0.00242056,0.0004120827,0.00006068698,0.0004112147,0.001712304,0.423866,0.02389884,0.361107,0.1857531,0.0001291245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01418554,0.0004008243,0.9552436,0.001238302,0.0001073238,0.0001808879,0.002702988,0.01233095,0.01360952],"genre_scores_gemma":[0.2654749,0.001048451,0.7225538,0.0004854789,0.0001145678,0.0003588596,0.004379262,0.001379187,0.004205368],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007264393,"threshold_uncertainty_score":0.02430189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05100085725790417,"score_gpt":0.3385381185704223,"score_spread":0.2875372613125181,"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."}}