{"id":"W2024806371","doi":"10.1145/2470654.2470696","title":"Individual user characteristics and information visualization","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":136,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Visualization; Human–computer interaction; Information visualization; Eye tracking; Bar chart; Perception; Relation (database); Cognition; Gaze; Task (project management); User interface; User modeling; Data visualization; Visual analytics; Creative visualization; Artificial intelligence; Data mining; Psychology","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":[0.00176323,0.0001802638,0.0002449452,0.001189865,0.0002867816,0.001132657,0.0001796579,0.0003730847,0.002670427],"category_scores_gemma":[0.02547994,0.0001141572,0.0002605141,0.0008380209,0.0002811787,0.0006393654,0.0004521529,0.000270929,0.0003905536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001474766,"about_ca_system_score_gemma":0.000129344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001020232,"about_ca_topic_score_gemma":0.001094195,"domain_scores_codex":[0.9987311,0.0004779315,0.0001531554,0.0001478516,0.0004010362,0.00008901943],"domain_scores_gemma":[0.9628173,0.02785128,0.003974402,0.001849766,0.002093986,0.001413302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004946629,0.0002568305,0.9170229,0.0002263391,0.0002307918,0.0003193721,0.005203824,0.0008545701,0.007526685,0.0003136031,0.0005717198,0.0669787],"study_design_scores_gemma":[0.000011606,0.0004024236,0.9912348,0.00002462658,0.00007020063,0.0009367474,0.001878251,0.001824332,0.001489295,0.0005691218,0.001515122,0.00004345085],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994371,0.0003548544,0.001812051,0.0000937976,0.000007378033,0.00002271808,0.0001369783,0.00006946966,0.003131839],"genre_scores_gemma":[0.9985244,0.0001123572,0.0008871708,0.00001932772,0.000006117921,0.00001207951,0.00006852821,0.000009762873,0.0003602977],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002670427,"threshold_uncertainty_score":0.009324908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01462599791917371,"score_gpt":0.2644998251327063,"score_spread":0.2498738272135326,"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."}}