{"id":"W4389539490","doi":"10.1145/3610548.3618225","title":"Neural Collision Fields for Triangle Primitives","year":2023,"lang":"en","type":"article","venue":"","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; High Performance Research Computing, Texas A and M University; Nvidia; National Science Foundation","keywords":"Polygon mesh; Collision; Artificial neural network; Computer science; Vertex (graph theory); Position (finance); Algorithm; Collision detection; Theoretical computer science; Artificial intelligence; Computer graphics (images)","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":[0.0004764146,0.0003161426,0.0003696978,0.0005906381,0.0005172343,0.0006550558,0.001519418,0.001118255,0.003745677],"category_scores_gemma":[0.002724761,0.0003166053,0.0003868431,0.0005974714,0.0008605804,0.00160846,0.00122043,0.0009115569,0.0002926418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001161913,"about_ca_system_score_gemma":0.0007669989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004152158,"about_ca_topic_score_gemma":0.004532186,"domain_scores_codex":[0.9997537,0.00003907027,0.000008395209,0.00003556975,0.0001332926,0.00003017838],"domain_scores_gemma":[0.9994764,0.0002482187,0.00005812239,0.00005725803,0.0001067029,0.00005325468],"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":[0.00004246709,0.00003011399,0.0004807452,0.00002354158,0.00001040451,0.00007181534,0.00005083629,0.9278055,0.002270946,0.04673842,0.0006953018,0.02177984],"study_design_scores_gemma":[0.000002986268,0.000006167496,0.00003037361,0.00000151142,8.248792e-7,0.00001109537,0.000003714728,0.9937115,0.0002833624,0.005683181,0.0002633938,0.000002038839],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0487632,0.0001217412,0.9450352,0.0002790785,0.00005941001,0.00004077804,0.0000716314,0.0002970922,0.005331783],"genre_scores_gemma":[0.8404232,0.0001728724,0.1529652,0.0002308239,0.00006556316,0.0001354713,0.0001499834,0.0001443549,0.005712653],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004152158,"threshold_uncertainty_score":0.01253051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02790046539280861,"score_gpt":0.2524380395539433,"score_spread":0.2245375741611347,"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."}}