{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006086432,0.0000441079,0.00007868822,0.0000597612,0.00003202656,0.0000154382,0.00004074221,0.00003241773,0.00002815052],"category_scores_gemma":[0.00002293296,0.00003725972,0.00007114662,0.0001555887,0.000002991573,0.00003076705,0.000007000309,0.00002762175,0.00004073482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005349104,"about_ca_system_score_gemma":0.000002232213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003583238,"about_ca_topic_score_gemma":0.00000659858,"domain_scores_codex":[0.9997122,0.000003158805,0.00007486246,0.00006335655,0.00004146537,0.0001049105],"domain_scores_gemma":[0.9998335,0.00006418745,0.000003876696,0.00006281361,0.00001341821,0.00002220576],"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":[0.000005066422,0.000005365808,0.00005231813,0.00003032425,0.00003504454,0.000001634951,0.0001676955,0.9512271,0.000762778,0.0001692961,0.02990199,0.01764135],"study_design_scores_gemma":[0.0001479448,0.00001225604,0.00007481563,0.00000370876,0.000009418037,1.417493e-7,0.00007319007,0.9962187,0.00212545,0.0001995841,0.00108063,0.00005418833],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6309475,0.0001047113,0.358668,0.0005746778,0.0002840788,0.0001374926,0.0000131671,0.001325942,0.007944391],"genre_scores_gemma":[0.9952921,0.00002736889,0.000596615,0.00003807827,0.00006236124,0.00001643157,0.00001684027,0.00001036924,0.003939832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3643445,"threshold_uncertainty_score":0.1519407,"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."}}