{"id":"W1977985708","doi":"10.1145/1274871.1274886","title":"Engaging viewers through nonphotorealistic visualizations","year":2007,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Visualization; Rendering (computer graphics); Perception; Human visual system model; Data visualization; Visual perception; Human–computer interaction; Computer graphics (images); Artificial intelligence; Computer vision; Image (mathematics); 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":[0.001212408,0.0009258484,0.0004571177,0.0006341427,0.0005255047,0.002457106,0.0008117321,0.0007113497,0.006361065],"category_scores_gemma":[0.006601035,0.0003686307,0.0006629808,0.0004771365,0.00137327,0.001939794,0.002523819,0.001179519,0.0006219349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002883611,"about_ca_system_score_gemma":0.0002747437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003456217,"about_ca_topic_score_gemma":0.0006254704,"domain_scores_codex":[0.9994104,0.0003047086,0.0000250153,0.0000720083,0.0001272047,0.00006069029],"domain_scores_gemma":[0.997048,0.001925273,0.000172589,0.0005318787,0.0001850725,0.0001372594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001372221,0.0003795067,0.004599688,0.001627665,0.0001802019,0.001525687,0.03596791,0.04298726,0.4356003,0.1145441,0.01159435,0.3496211],"study_design_scores_gemma":[0.0008579253,0.001589591,0.01776182,0.0006391869,0.000386935,0.00350616,0.01304676,0.2427982,0.2065303,0.2442,0.2681167,0.0005663665],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2696453,0.0007672753,0.7038093,0.001378774,0.0001617731,0.0002295751,0.0003382033,0.003592795,0.02007696],"genre_scores_gemma":[0.6047998,0.0006065779,0.3890321,0.0002314275,0.00008151566,0.0002997596,0.0001906168,0.0006647172,0.00409345],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006361065,"threshold_uncertainty_score":0.02127987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03422264521007926,"score_gpt":0.3505516590489779,"score_spread":0.3163290138388986,"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."}}