{"id":"W2781859200","doi":"10.1145/3197517.3201281","title":"Eulerian-on-lagrangian cloth simulation","year":2018,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Constraint (computer-aided design); Lagrangian; Eulerian path; Augmented Lagrangian method; Set (abstract data type); Computer science; Motion (physics); Mathematics; Algorithm; Geometry; Applied mathematics; Artificial intelligence; Programming language","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026714,0.0003460022,0.0005022603,0.0003659935,0.0004063979,0.0007830485,0.001353795,0.001030863,0.00482006],"category_scores_gemma":[0.001371439,0.0003494631,0.0005773792,0.0002973424,0.0008434203,0.00114042,0.002336097,0.0007483934,0.0007883185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005664579,"about_ca_system_score_gemma":0.001002312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003187958,"about_ca_topic_score_gemma":0.002993099,"domain_scores_codex":[0.9997765,0.00004419585,0.00001043766,0.00003244969,0.00009779736,0.00003844745],"domain_scores_gemma":[0.9997215,0.0000751475,0.00002563269,0.00007329032,0.00004868898,0.00005576441],"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":[0.00004476323,0.00004455734,0.0007629264,0.00007062698,0.00001604522,0.0001776082,0.0001406027,0.9224146,0.006740771,0.05396443,0.001441064,0.01418205],"study_design_scores_gemma":[0.000008237458,0.000007408528,0.00004930018,0.000004998063,0.000001902141,0.00002309398,0.000009028065,0.9933853,0.0007400394,0.003923835,0.001842245,0.000004770213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05704142,0.0001924681,0.9099122,0.0003840707,0.0001262086,0.0000854203,0.0002594102,0.0008444345,0.0311543],"genre_scores_gemma":[0.7096196,0.0004817949,0.2690155,0.0003060171,0.0000460158,0.0002341593,0.000462773,0.0004914535,0.01934271],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00482006,"threshold_uncertainty_score":0.01612467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02348825622972735,"score_gpt":0.2565433828579045,"score_spread":0.2330551266281771,"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."}}