{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005096633,0.00105937,0.0006793872,0.003273264,0.001486373,0.008075941,0.002938677,0.002234536,0.007060037],"category_scores_gemma":[0.01420708,0.0007496711,0.001942445,0.001731602,0.007775326,0.01197655,0.003494132,0.003059291,0.00139221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002798576,"about_ca_system_score_gemma":0.00220391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007486014,"about_ca_topic_score_gemma":0.005101723,"domain_scores_codex":[0.9969956,0.001486955,0.0001446186,0.0005511229,0.0006589232,0.0001627476],"domain_scores_gemma":[0.993361,0.003829879,0.0003424471,0.001151378,0.0009543301,0.0003609106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001855455,0.00004407678,0.0007288775,0.0001810546,0.000036607,0.00009711945,0.0023293,0.01172259,0.0006635423,0.9554322,0.002586548,0.02615955],"study_design_scores_gemma":[0.00001511406,0.0000312677,0.0003766176,0.0001162084,0.000016758,0.0001161831,0.0005907828,0.0717081,0.0004883927,0.911479,0.0150306,0.0000310315],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004421457,0.0004107763,0.9731889,0.003891949,0.00006862535,0.0001234154,0.00009259702,0.0005071675,0.0172951],"genre_scores_gemma":[0.2521492,0.0008546289,0.7418507,0.0006311526,0.0001028383,0.0005096644,0.0002375419,0.0002019407,0.003462398],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008075941,"threshold_uncertainty_score":0.02695388,"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."}}