{"id":"W2545503847","doi":"10.3390/informatics3040020","title":"Supporting Sensemaking of Complex Objects with Visualizations: Visibility and Complementarity of Interactions","year":2016,"lang":"en","type":"article","venue":"Informatics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Sensemaking; Computer science; Human–computer interaction; Complementarity (molecular biology); Visualization; Visual analytics; Usability; Visibility; Representation (politics); Information visualization; Data science; Knowledge management; 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":[0.01058843,0.001719847,0.0008985825,0.002143249,0.00152437,0.008782516,0.001647992,0.001491152,0.002889573],"category_scores_gemma":[0.04519525,0.001173484,0.001198279,0.001206586,0.003528683,0.008602615,0.006969819,0.001531782,0.0004063699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005292665,"about_ca_system_score_gemma":0.001251394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006055416,"about_ca_topic_score_gemma":0.0008810695,"domain_scores_codex":[0.9907762,0.00619843,0.0005994482,0.0007865212,0.001224082,0.0004153303],"domain_scores_gemma":[0.9460772,0.0424875,0.003002081,0.005314094,0.001971219,0.001147917],"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":[0.001614707,0.0009284899,0.02366785,0.004037003,0.000386601,0.001757236,0.1861191,0.01345473,0.1425702,0.1249108,0.004241139,0.4963121],"study_design_scores_gemma":[0.001288295,0.003939638,0.05147417,0.004554997,0.001525563,0.006559496,0.08902793,0.142884,0.1325631,0.3293004,0.2356734,0.001208971],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2782075,0.001265138,0.6992024,0.001928908,0.0001002865,0.0004552306,0.00008158303,0.002200033,0.01655897],"genre_scores_gemma":[0.6223063,0.0004296386,0.3751202,0.0001461277,0.00002848288,0.0004329753,0.00007315809,0.0002350713,0.001228044],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01058843,"threshold_uncertainty_score":0.05599761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04186532548949052,"score_gpt":0.3709616049255003,"score_spread":0.3290962794360098,"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."}}