{"id":"W2017311408","doi":"10.1145/2451236.2451241","title":"Closest point turbulence for liquid surfaces","year":2013,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Turbulence; Embedding; Surface (topology); Algorithm; Point (geometry); Extension (predicate logic); Generalization; Operator (biology); Advection; Computer science; Field (mathematics); Resolution (logic); Mathematics; Mathematical analysis; Geometry; Physics; Artificial intelligence; Mechanics; Pure mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004049759,0.0004444768,0.0005195932,0.0005357285,0.0005810701,0.001125434,0.001358589,0.00119337,0.002747622],"category_scores_gemma":[0.002199995,0.0003193202,0.0008399604,0.0002991628,0.001158261,0.00184536,0.002336215,0.001786337,0.0005964388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006654626,"about_ca_system_score_gemma":0.0006764495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001546824,"about_ca_topic_score_gemma":0.0007084804,"domain_scores_codex":[0.9996332,0.00006607932,0.0000113094,0.00004531364,0.000212389,0.00003174345],"domain_scores_gemma":[0.9995158,0.0002169681,0.00004688742,0.00008806631,0.00007761663,0.00005469408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009351697,0.0000833896,0.0005343665,0.00006685715,0.00002127466,0.0002292476,0.0002891104,0.6092519,0.03608776,0.3176799,0.001088425,0.03457427],"study_design_scores_gemma":[0.000009224567,0.0000134919,0.00002362356,0.000002701345,0.000001128301,0.00001916623,0.000008853625,0.979634,0.002531168,0.01676395,0.000985863,0.000006842687],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03466019,0.00007341645,0.9603397,0.0002042546,0.00005830628,0.00004185742,0.00001759703,0.0004072976,0.00419729],"genre_scores_gemma":[0.5024905,0.0001924726,0.489592,0.0001537288,0.00006517896,0.0001605429,0.0000838885,0.0003818084,0.006879834],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002747622,"threshold_uncertainty_score":0.009191751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02497463086166126,"score_gpt":0.2815502798151003,"score_spread":0.2565756489534391,"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."}}