{"id":"W2058203255","doi":"10.1109/tvcg.2011.279","title":"Empirical Studies in Information Visualization: Seven Scenarios","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":628,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Visualization; Computer science; Information visualization; Data visualization; Visual analytics; Data science; Creative visualization; Empirical research; Human–computer interaction; Information retrieval; Data mining","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":[0.1055358,0.001290904,0.000940321,0.005523612,0.00457863,0.009900438,0.00298305,0.006914652,0.003533819],"category_scores_gemma":[0.1767346,0.001051532,0.001624978,0.008228472,0.00726707,0.01399221,0.007240496,0.004335442,0.00056329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00705865,"about_ca_system_score_gemma":0.003560091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002345707,"about_ca_topic_score_gemma":0.00309189,"domain_scores_codex":[0.8278415,0.1513237,0.006607634,0.002289474,0.009888696,0.002049059],"domain_scores_gemma":[0.6013031,0.3537358,0.008942896,0.01017215,0.02099109,0.004854914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.002955034,0.006344605,0.08085155,0.007587693,0.0004379682,0.004637051,0.07361854,0.02441181,0.00316654,0.6144315,0.02702234,0.1545353],"study_design_scores_gemma":[0.002501285,0.00785506,0.04106385,0.01563143,0.000510219,0.004977528,0.1806663,0.07007537,0.01126542,0.4956471,0.1689731,0.0008333398],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.636342,0.02185843,0.1762145,0.06566568,0.0006555218,0.008006361,0.001747588,0.0003934084,0.08911649],"genre_scores_gemma":[0.857495,0.006776557,0.1241996,0.002535538,0.000172811,0.005944768,0.0009393336,0.00006551819,0.001870869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1055358,"threshold_uncertainty_score":0.5581336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08538256592749338,"score_gpt":0.3483762672902525,"score_spread":0.2629937013627591,"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."}}