{"id":"W1580110518","doi":"10.1117/12.2184179","title":"Collaborative interactive visualization: exploratory concept","year":2015,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Sensemaking; Visualization; Computer science; Human–computer interaction; Context (archaeology); Comprehension; Data visualization; Data science; Knowledge management; Multimedia; Artificial intelligence","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":[0.005595128,0.000794819,0.0004771306,0.002370019,0.001767568,0.008593262,0.002155411,0.001449298,0.009173232],"category_scores_gemma":[0.007591123,0.0005624563,0.001012652,0.002117094,0.004868034,0.00824611,0.005132694,0.001231653,0.001320602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001064535,"about_ca_system_score_gemma":0.002008963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001219582,"about_ca_topic_score_gemma":0.001116195,"domain_scores_codex":[0.9975767,0.001306108,0.00007548984,0.0003209749,0.0005863821,0.0001343385],"domain_scores_gemma":[0.9959934,0.002247689,0.0001988373,0.0008092098,0.0004897427,0.0002610101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002271413,0.0002030145,0.002793199,0.0009628884,0.00009835065,0.0006604553,0.03457353,0.005251998,0.008521693,0.7165639,0.01536763,0.2147762],"study_design_scores_gemma":[0.0001169663,0.0002657169,0.00193465,0.0008891876,0.00007626753,0.001704224,0.01289517,0.06327379,0.006870958,0.6284286,0.283417,0.0001274036],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01590319,0.001392003,0.9318526,0.001662632,0.0001526753,0.0003895199,0.0002263306,0.001775873,0.04664524],"genre_scores_gemma":[0.2492789,0.001533268,0.738342,0.0002797075,0.0001487971,0.0007594709,0.0004081984,0.0003898253,0.008859735],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009173232,"threshold_uncertainty_score":0.03068757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02212409045006856,"score_gpt":0.3119063222852766,"score_spread":0.289782231835208,"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."}}