{"id":"W4413258532","doi":"10.1109/tvcg.2025.3599458","title":"VIVA: Virtual Healthcare Interactions Using Visual Analytics, With Controllability Through Configuration","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Controllability; Computer science; Visual analytics; Human–computer interaction; Visualization; Data visualization; Analytics; Interactive visual analysis; Computer graphics (images); Artificial intelligence; Data mining; Mathematics","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":[0.005949046,0.001491027,0.0004230877,0.001327233,0.001130877,0.005516144,0.00274665,0.001207116,0.005350615],"category_scores_gemma":[0.01505649,0.0009564693,0.0009691623,0.0005886601,0.003254919,0.004404631,0.007348773,0.002033416,0.001123608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009284141,"about_ca_system_score_gemma":0.001643478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001451079,"about_ca_topic_score_gemma":0.001507503,"domain_scores_codex":[0.9938974,0.003849057,0.0002816352,0.0006833343,0.0009055023,0.0003830564],"domain_scores_gemma":[0.9903142,0.006160663,0.0004915497,0.001774931,0.0005843448,0.0006742325],"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":[0.001907717,0.0008670781,0.01293142,0.001903479,0.0002944238,0.002089213,0.06341667,0.07092896,0.1053783,0.2601445,0.03460819,0.4455301],"study_design_scores_gemma":[0.0005545709,0.001411124,0.008328577,0.001025027,0.0002243472,0.001950467,0.01019551,0.2966025,0.0627123,0.2503379,0.3661335,0.0005241177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03173567,0.0001357137,0.9438938,0.001134017,0.00007535459,0.0005554071,0.0002589224,0.009712053,0.01249901],"genre_scores_gemma":[0.4247857,0.0002420162,0.5632908,0.0005922961,0.00006669584,0.001353722,0.0007404807,0.002150931,0.006777391],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005949046,"threshold_uncertainty_score":0.03146195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02750381051759542,"score_gpt":0.3320362473516223,"score_spread":0.3045324368340269,"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."}}