{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06041691,0.002118428,0.001391813,0.002897139,0.002493392,0.01007896,0.006131672,0.005108402,0.008048314],"category_scores_gemma":[0.1267129,0.00295755,0.003819742,0.001443149,0.01048531,0.01555324,0.009158936,0.007275172,0.002645828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005019111,"about_ca_system_score_gemma":0.008496432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003844251,"about_ca_topic_score_gemma":0.003728446,"domain_scores_codex":[0.9152511,0.05356823,0.004813375,0.007331647,0.01728183,0.001753828],"domain_scores_gemma":[0.8712171,0.07947998,0.005792633,0.02521351,0.01579158,0.002505217],"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":[0.0002557858,0.0002951684,0.002716126,0.0004743158,0.0001297795,0.0002940819,0.00309846,0.1018873,0.00440619,0.8296893,0.002588611,0.054165],"study_design_scores_gemma":[0.0001287356,0.0002759007,0.0002758476,0.0003184357,0.00007201659,0.0001787724,0.0002531892,0.4348398,0.003605825,0.5432078,0.01676587,0.00007784519],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001312613,0.00004138129,0.9957503,0.0005430722,0.00001625554,0.0002713542,0.00003375595,0.0002597496,0.001771546],"genre_scores_gemma":[0.04725003,0.00006659835,0.9492983,0.0002721291,0.00002641589,0.001131987,0.0001374232,0.0001917556,0.001625389],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06041691,"threshold_uncertainty_score":0.319519,"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."}}