{"id":"W2142493242","doi":"10.1109/tvcg.2009.111","title":"A Nested Model for Visualization Design and Validation","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":899,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Visualization; Data visualization; Domain (mathematical analysis); Focus (optics); Vocabulary; Visual analytics; Task (project management); Data mining; Data modeling; Upstream (networking); Information visualization; Creative visualization; Data science; Human–computer interaction; Machine learning; Software engineering; Systems engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003289182,0.0002374559,0.0002092103,0.000482221,0.0004246107,0.0004659212,0.0002162535,0.0001329877,0.000002153149],"category_scores_gemma":[0.000007134483,0.0002466437,0.00006339836,0.0008111274,0.00004904002,0.0008062627,0.000004088774,0.00007919016,0.000001727843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001939472,"about_ca_system_score_gemma":0.00005164849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001662511,"about_ca_topic_score_gemma":0.000001725009,"domain_scores_codex":[0.9985013,0.000122064,0.0003750822,0.0005158244,0.0002664405,0.000219269],"domain_scores_gemma":[0.9990599,0.0001189538,0.0001331362,0.0002812232,0.0002568809,0.0001499732],"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":[0.00002490428,0.0002418825,0.000006916378,0.00002828663,0.00002263667,5.669662e-7,0.0008416979,0.03157609,0.00005563272,0.9515345,0.0004106765,0.01525627],"study_design_scores_gemma":[0.0007914663,0.000381751,0.00005025267,0.00003547006,0.00003616482,0.000009250825,0.00001028289,0.9893894,0.001673134,0.007086163,0.0002552147,0.0002814922],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0007380386,0.00002357207,0.9980259,0.0001492778,0.0001900493,0.0005133341,0.00001270375,0.000339076,0.00000802775],"genre_scores_gemma":[0.9487202,0.000543943,0.04543097,0.004913201,0.00005870572,0.00004597572,0.00008662784,0.00003332432,0.000167092],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9578133,"threshold_uncertainty_score":0.9999986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04481429713190511,"score_gpt":0.3127659514960759,"score_spread":0.2679516543641708,"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."}}