{"id":"W2153836330","doi":"10.1109/tvcg.2007.70436","title":"Visual Perception and Mixed-Initiative Interaction for Assisted Visualization Design","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Waterloo; National Science Foundation","keywords":"Computer science; Visualization; Human–computer interaction; Context (archaeology); Salient; Perception; Data visualization; Creative visualization; Domain (mathematical analysis); Data science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003111216,0.0003108336,0.0002817854,0.0006805884,0.0008555098,0.0003066092,0.0001957574,0.0001753701,0.00001146184],"category_scores_gemma":[0.00001388997,0.0003252809,0.0001000339,0.0009271064,0.0001440318,0.001169482,0.00001003494,0.0001423195,0.000007240277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006507611,"about_ca_system_score_gemma":0.00008227527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008397061,"about_ca_topic_score_gemma":0.000009747281,"domain_scores_codex":[0.9979689,0.0002931439,0.0004846119,0.000646539,0.0003466859,0.0002601199],"domain_scores_gemma":[0.9986944,0.0002862723,0.0002101365,0.0002390764,0.0003920144,0.0001781239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003362212,0.002055473,0.0003504273,0.0002972077,0.0004099599,0.00001751562,0.0101095,0.005660021,0.0005855386,0.8565131,0.005474827,0.1181902],"study_design_scores_gemma":[0.00100868,0.0006869041,0.001584945,0.00005688599,0.00004547956,0.00008325179,0.0001186004,0.9928496,0.00170839,0.0004278356,0.001057169,0.0003722205],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006782039,0.0000197126,0.9915162,0.00007072194,0.0006964425,0.0005063807,0.00002182493,0.0003690911,0.00001762606],"genre_scores_gemma":[0.987418,0.0008745042,0.009455374,0.001841788,0.0001002171,0.0000763939,0.0001088313,0.00004158319,0.00008332681],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9871896,"threshold_uncertainty_score":0.99992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06620721598083383,"score_gpt":0.3252732925827256,"score_spread":0.2590660766018917,"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."}}