{"id":"W2974882494","doi":"10.1109/cjece.2019.2917394","title":"Evolution Surfaces for Spatiotemporal Visualization of Vortex Features","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Electrical and Computer Engineering","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta; CMC Microsystems","keywords":"Visualization; Flow visualization; Computer science; Vortex; Rendering (computer graphics); Reynolds number; Data visualization; Flow (mathematics); Turbulence; Artificial intelligence; Mathematics; Physics; Geometry; Mechanics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0001122375,0.00008270067,0.0001703416,0.0002394368,0.00004050039,0.00007929678,0.0002410995,0.00004570839,5.718941e-7],"category_scores_gemma":[0.00004124322,0.00007909835,0.00006092352,0.000452899,0.00001114939,0.0001956745,0.00001884331,0.00007608133,4.802062e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000242741,"about_ca_system_score_gemma":0.0001660467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008881582,"about_ca_topic_score_gemma":0.00002658639,"domain_scores_codex":[0.9993746,0.00001478096,0.0002646738,0.000109577,0.00009722263,0.0001391057],"domain_scores_gemma":[0.9992901,0.00005993368,0.0001231523,0.00005617123,0.000211971,0.0002586681],"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":[0.000009256439,0.00001844925,0.006885333,0.0001056062,0.00005416064,0.00001154933,0.0007620884,0.008489,0.0005510675,0.96538,0.001984571,0.01574898],"study_design_scores_gemma":[0.0001604052,0.0004449977,0.01051438,0.00002885822,0.0000058317,0.00001989071,8.715974e-7,0.9851505,0.001129811,0.001217454,0.001234817,0.00009216626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02246588,0.0007461635,0.9763322,0.000221353,0.0001332866,0.00007270611,0.000001430912,0.00002401665,0.00000291425],"genre_scores_gemma":[0.9705695,0.00001574306,0.02914394,0.0001145389,0.0001468999,8.173798e-7,0.000001242282,0.00000611956,0.000001193222],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9766615,"threshold_uncertainty_score":0.3225537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0104982849040177,"score_gpt":0.2223750423458674,"score_spread":0.2118767574418497,"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."}}