{"id":"W1979442950","doi":"10.1109/vast.2010.5653060","title":"Model based interactive analysis of interwoven, imprecise narratives: VAST 2010 mini challenge 1 award: Outstanding interaction model","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Focus (optics); Synchronizing; Visual analytics; Dependency (UML); Narrative; Data visualization; Variety (cybernetics); Visualization; Process (computing); Data science; Analytics; Cluster analysis; Human–computer interaction; Information retrieval; Artificial intelligence; Programming language","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":[0.005385359,0.0007590761,0.0006342754,0.001464659,0.001304882,0.005261459,0.002337063,0.001506108,0.007245672],"category_scores_gemma":[0.02006415,0.0005007538,0.001433217,0.001319464,0.001826174,0.007371155,0.005246645,0.001747917,0.001367412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002029052,"about_ca_system_score_gemma":0.001924802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009138392,"about_ca_topic_score_gemma":0.01343285,"domain_scores_codex":[0.9960045,0.002209288,0.0001760224,0.0005527827,0.0009105298,0.000146741],"domain_scores_gemma":[0.9887482,0.007939099,0.000359758,0.001571494,0.001054185,0.0003273067],"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":[0.0006991679,0.0003574351,0.006371375,0.0009551389,0.0002354901,0.001209058,0.01831709,0.1312844,0.01140789,0.4663003,0.0710489,0.2918138],"study_design_scores_gemma":[0.00006306871,0.00005941568,0.001039294,0.0001394432,0.00005574581,0.000287194,0.003082501,0.7218174,0.0045375,0.2042798,0.06456902,0.00006965495],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03391638,0.0004530587,0.9436944,0.004949993,0.0001298652,0.0002566235,0.00182872,0.003107285,0.01166361],"genre_scores_gemma":[0.3062113,0.0005775871,0.6781239,0.0004111697,0.00007299008,0.0004533373,0.004249671,0.0007663837,0.009133599],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009138392,"threshold_uncertainty_score":0.02848083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0505723566965089,"score_gpt":0.3459550518725201,"score_spread":0.2953826951760112,"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."}}