{"id":"W2037205988","doi":"10.1109/tvcg.2012.204","title":"Beyond Mouse and Keyboard: Expanding Design Considerations for Information Visualization Interactions","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":210,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Interactivity; Human–computer interaction; Visualization; Pointer (user interface); Data science; Interaction design; Data visualization; Information visualization; World Wide Web; 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":[0.009191188,0.002632804,0.00123543,0.002560491,0.002145974,0.008949819,0.003011769,0.003133978,0.007456086],"category_scores_gemma":[0.03625822,0.001356457,0.001428938,0.001287905,0.003471667,0.01312482,0.003773902,0.003042667,0.001620983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001318534,"about_ca_system_score_gemma":0.001372104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001633669,"about_ca_topic_score_gemma":0.00198169,"domain_scores_codex":[0.9900525,0.005527856,0.000732072,0.000855273,0.002399804,0.0004324618],"domain_scores_gemma":[0.9699864,0.02031188,0.001252668,0.002933555,0.004600179,0.0009153484],"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":[0.001134109,0.0003870577,0.009121629,0.005202361,0.0001448553,0.001711411,0.04355932,0.008899093,0.0497386,0.3904859,0.01686353,0.4727522],"study_design_scores_gemma":[0.0003403533,0.002482778,0.01172289,0.005849536,0.0007609262,0.007141913,0.01637281,0.1349827,0.03295995,0.3400026,0.4468371,0.0005465507],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04041646,0.005991071,0.9130276,0.008486961,0.0003477073,0.0003888633,0.0001137607,0.00307547,0.02815214],"genre_scores_gemma":[0.4121137,0.004594863,0.5706467,0.001688299,0.0003436884,0.0009237575,0.0002218234,0.00110972,0.008357476],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009191188,"threshold_uncertainty_score":0.04860824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04117507242616682,"score_gpt":0.3134194433823437,"score_spread":0.2722443709561769,"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."}}