{"id":"W4230323307","doi":"10.1057/ivs.2008.28","title":"Building and Applying a Human Cognition Model for Visual Analytics","year":2009,"lang":"en","type":"article","venue":"Information Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"U.S. Department of Homeland Security","keywords":"Visual analytics; Computer science; Visualization; Cultural analytics; Analytics; Human–computer interaction; Data science; Visual reasoning; Cognition; Analytic reasoning; Perception; Interactive visual analysis; Artificial intelligence; Cognitive science; Semantic analytics; Reasoning system; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003250725,0.0001326012,0.000131386,0.0003578828,0.0003263853,0.0006123267,0.0001906193,0.00007576989,0.000002533846],"category_scores_gemma":[0.0001080629,0.0001432312,0.00003734651,0.0004783039,0.000018871,0.004090906,0.00004897294,0.00004350471,0.000006574881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003646273,"about_ca_system_score_gemma":0.00003796439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001182253,"about_ca_topic_score_gemma":8.970683e-7,"domain_scores_codex":[0.9989095,0.00001963732,0.0004599647,0.0001629671,0.0002645044,0.0001834125],"domain_scores_gemma":[0.9991627,0.00002811464,0.0002497689,0.0001512363,0.0003265843,0.00008154476],"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":[0.000004434308,0.0000407033,0.00003072228,0.00003990096,0.000008384947,9.578378e-8,0.0007637222,0.008179309,0.0007332208,0.9572582,0.0005936311,0.03234766],"study_design_scores_gemma":[0.0005346438,0.00008288635,0.0001403601,0.00002652592,0.00001859282,0.00000267845,0.00004746471,0.9768704,0.0007667353,0.0196234,0.00170568,0.0001806564],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002119527,0.000006945588,0.99661,0.0001297909,0.00004499332,0.0003941532,0.00001319098,0.0002385152,0.000442871],"genre_scores_gemma":[0.9547133,0.0000162539,0.04231519,0.002264773,0.00004287191,0.00003019024,0.0005688388,0.000006783947,0.00004177435],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9686911,"threshold_uncertainty_score":0.590468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03433443006959723,"score_gpt":0.3538639534782666,"score_spread":0.3195295234086694,"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."}}