{"id":"W2513074232","doi":"10.1109/tvcg.2016.2598866","title":"Decal-Maps: Real-Time Layering of Decals on Surfaces for Multivariate Visualization","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures; CMG Reservoir Simulation Foundation","keywords":"Visualization; Glyph (data visualization); Computer science; Data visualization; Layering; Computer graphics (images); Multivariate statistics; Set (abstract data type); Information visualization; Artificial intelligence; Data mining; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003659923,0.0002700041,0.0003239637,0.0005399244,0.0002644279,0.0001536611,0.000363033,0.0001459185,0.00001704654],"category_scores_gemma":[0.00002148528,0.0002176346,0.0001300965,0.000827414,0.00009462409,0.0005511762,0.00001010066,0.00005565134,0.00001275172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003087541,"about_ca_system_score_gemma":0.00005225984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001707706,"about_ca_topic_score_gemma":0.000009578244,"domain_scores_codex":[0.9980702,0.0001624891,0.0005715162,0.0005536462,0.0003769571,0.0002651437],"domain_scores_gemma":[0.9982349,0.0004941018,0.0002555149,0.0004251098,0.0004416251,0.000148747],"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":[0.00006221249,0.0004828449,0.0000749578,0.00008030306,0.00009394227,0.0000010525,0.0004703775,0.00151393,0.002482928,0.9784548,0.0004285053,0.01585413],"study_design_scores_gemma":[0.001384077,0.0005394677,0.0002199566,0.0002299503,0.00003367251,0.000002894853,0.00001249042,0.9671059,0.02710514,0.001460741,0.00156801,0.0003377115],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007566277,0.000008369283,0.9911646,0.00009470488,0.000388515,0.000350474,0.0001049011,0.000277625,0.00004450582],"genre_scores_gemma":[0.9904057,0.0007515561,0.007404799,0.0009163064,0.00006425202,0.00004349209,0.00005098684,0.00005819479,0.0003046613],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9837598,"threshold_uncertainty_score":0.887488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02726732029595989,"score_gpt":0.311272715879734,"score_spread":0.2840053955837741,"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."}}