{"id":"W4225371802","doi":"10.1145/3528223.3530108","title":"Neural dual contouring","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Google","keywords":"Computer science; Contouring; Grid; Polygon mesh; Vertex (graph theory); Convolutional neural network; Regular grid; Marching cubes; Point cloud; Artificial neural network; Intersection (aeronautics); Artificial intelligence; Algorithm; Surface (topology); Enhanced Data Rates for GSM Evolution; Voxel; Surface reconstruction; Octree; Theoretical computer science; Mathematics; Computer graphics (images); Visualization; Geometry","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":[0.00008131645,0.00009640099,0.00009910712,0.0002126956,0.0003533316,0.00001858363,0.0001521545,0.00002660952,0.0002311467],"category_scores_gemma":[0.000003293916,0.0001102568,0.0001400646,0.0003965478,0.00001493263,0.00005029737,0.000003820629,0.0004116947,0.000008135977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002898596,"about_ca_system_score_gemma":0.000004618829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002001657,"about_ca_topic_score_gemma":0.00002708409,"domain_scores_codex":[0.999386,0.00002217298,0.0001251062,0.0001211495,0.0001838048,0.0001617635],"domain_scores_gemma":[0.9995953,0.00004587375,0.000009715669,0.0002884643,0.00001291811,0.00004770335],"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":[0.000004034301,0.00002938236,0.0000252599,0.000005999106,0.00006830307,0.000007716524,0.0001389057,0.9905398,0.0002119938,0.00004850185,0.0001330311,0.008787111],"study_design_scores_gemma":[0.0003121909,0.00006395424,0.0001260956,0.000004641727,0.00009375081,0.00002064206,0.000288703,0.9949886,0.0006002758,0.0009986652,0.002246734,0.0002557433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.555529,0.0003674849,0.4403067,0.000887413,0.0008702063,0.0001011847,0.00009155134,0.001062749,0.0007837152],"genre_scores_gemma":[0.9992449,0.00006047348,0.0003050913,0.0001701775,0.00002768842,0.00003612905,0.000006828204,0.00002515187,0.0001235782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4437159,"threshold_uncertainty_score":0.4496144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01799305350801736,"score_gpt":0.2156001845305886,"score_spread":0.1976071310225713,"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."}}