{"id":"W6963356793","doi":"10.20380/gi2021.31","title":"Contour Line Stylization to Visualize Multivariate Information","year":2021,"lang":"en","type":"article","venue":"Canada Human-Computer Communications Society","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Interpretability; Contour line; Geospatial analysis; Visualization; Clutter; Margin (machine learning); Pattern recognition (psychology); Data visualization; Spatial analysis","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":[0.0002523584,0.0001782676,0.0002056977,0.0000636948,0.0006976887,0.0005454242,0.00195827,0.00007182275,0.00003908165],"category_scores_gemma":[0.00006060723,0.000203676,0.00009967159,0.001013633,0.00004274782,0.00100186,0.001425982,0.0001795338,0.00002974576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003223928,"about_ca_system_score_gemma":0.0009364276,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02125036,"about_ca_topic_score_gemma":0.04226896,"domain_scores_codex":[0.9983699,0.0001632972,0.0005279152,0.0002714658,0.0004034238,0.0002640082],"domain_scores_gemma":[0.9963834,0.0001174492,0.0001846023,0.00227041,0.0008372956,0.000206888],"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":[0.000001204528,0.0002266669,0.0002445512,0.00005734997,0.0001587547,0.000004394705,0.00560574,0.00317783,0.000675077,0.5773444,0.3897144,0.0227897],"study_design_scores_gemma":[0.0003732716,0.00001340506,0.001007115,0.00003085155,0.00001182404,0.000004744943,0.0001760611,0.5186798,0.0003711822,0.0003336864,0.4787287,0.0002693585],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003501383,0.00008528696,0.9908635,0.007143832,0.0002699191,0.0001785926,0.00004672695,0.0001823688,0.0008796419],"genre_scores_gemma":[0.2688542,0.0001941131,0.6813549,0.04529692,0.0002026571,0.0000566917,0.002811014,0.00003205356,0.00119746],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5770106,"threshold_uncertainty_score":0.9852672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03712281894165109,"score_gpt":0.3217405188139579,"score_spread":0.2846176998723068,"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."}}