{"id":"W2101647284","doi":"10.1109/vis.2003.10030","title":"A Parallel Coordinates Interface for Exploratory Volume Visualization","year":2003,"lang":"en","type":"article","venue":"IEEE Visualization","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Volume rendering; Visualization; Rendering (computer graphics); Parallel coordinates; Data visualization; Computer graphics (images); Volume (thermodynamics); Undoing; Scientific visualization; Parallel rendering; Human–computer interaction; Computational science; Artificial intelligence","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":[0.001112367,0.001982162,0.001002592,0.001358554,0.001120019,0.002559189,0.002912302,0.00168023,0.05221972],"category_scores_gemma":[0.005724523,0.00110277,0.001153912,0.001402406,0.0008042779,0.003081803,0.004994432,0.002138753,0.01301098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005418587,"about_ca_system_score_gemma":0.0009527022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00228465,"about_ca_topic_score_gemma":0.002605297,"domain_scores_codex":[0.9987937,0.0002320779,0.0001089416,0.0001269507,0.0006632559,0.00007500169],"domain_scores_gemma":[0.9982049,0.0006472949,0.00006823076,0.0004602553,0.0004725442,0.000146734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001043672,0.000250598,0.001226653,0.0004823548,0.0001093218,0.001108842,0.001020405,0.0219313,0.03790485,0.1186265,0.2820408,0.5342546],"study_design_scores_gemma":[0.000548175,0.0001860723,0.0005840149,0.0001147329,0.0000657808,0.001322072,0.000135906,0.431698,0.04147672,0.08165323,0.4420137,0.0002016464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001096227,0.0001076652,0.9539399,0.0001577624,0.0001386305,0.00009503276,0.0005399138,0.03944194,0.004482908],"genre_scores_gemma":[0.0317685,0.0004024868,0.9411407,0.0002178555,0.0001700853,0.000754179,0.002585644,0.0103066,0.01265397],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05221972,"threshold_uncertainty_score":0.1746923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03501979058141939,"score_gpt":0.3314202639472411,"score_spread":0.2964004733658217,"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."}}