{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002360002,0.00009034466,0.00009512184,0.000210987,0.0000882887,0.0002286148,0.0004589816,0.00002605097,0.00005061224],"category_scores_gemma":[0.00004555223,0.00006932369,0.00002723365,0.002102894,0.0000308594,0.000408242,0.000145793,0.00006410416,0.0002311029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001756126,"about_ca_system_score_gemma":0.00009643072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001491011,"about_ca_topic_score_gemma":0.00002009159,"domain_scores_codex":[0.999102,0.00002721205,0.0001064766,0.0002688757,0.0002864275,0.0002090356],"domain_scores_gemma":[0.9993678,0.00009584332,0.00004366995,0.0003342932,0.00007094686,0.0000874795],"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":[0.00004331039,0.000744131,0.01017629,0.0001401706,0.0001396525,0.0002582998,0.0006545032,0.107969,0.002951324,0.5312319,0.01215727,0.333534],"study_design_scores_gemma":[0.00006338369,0.00005496868,0.0003687908,0.000009422008,0.000003846254,0.0000010222,0.00004094742,0.9859825,0.0107732,0.0002018942,0.002381713,0.0001182546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004857142,0.000001378985,0.9925411,0.000539612,0.00005387492,0.00004351616,0.000001654455,0.0004859026,0.001475855],"genre_scores_gemma":[0.9853801,0.000009417848,0.012402,0.0006612735,0.00002378732,0.000002112823,0.0000120191,0.000007737694,0.001501537],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.980523,"threshold_uncertainty_score":0.2970437,"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."}}