{"id":"W2947464908","doi":"10.1111/cgf.14020","title":"Learning Generative Models of 3D Structures","year":2020,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"China National Funds for Distinguished Young Scientists; National Natural Science Foundation of China","keywords":"Computer science; Generative grammar; Computer graphics; Generative model; Artificial intelligence; Probabilistic logic; Graphics; Generative Design; Rendering (computer graphics); Human–computer interaction; Computer graphics (images)","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00003229682,0.0001124967,0.0001870025,0.00007710776,0.00005073629,0.0000202868,0.000129852,0.00005326364,0.000006529846],"category_scores_gemma":[0.000002745322,0.000107962,0.00009798256,0.0002356208,0.00002313634,0.00006957717,0.0000458842,0.0001949899,0.000002065451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004219536,"about_ca_system_score_gemma":0.000005541604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003995553,"about_ca_topic_score_gemma":0.000002001458,"domain_scores_codex":[0.9994156,0.00001621511,0.0001671789,0.0001339573,0.0001134047,0.0001536117],"domain_scores_gemma":[0.9997551,0.00001603235,0.00002634375,0.00009294129,0.00004598471,0.000063585],"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":[0.000001313649,0.000002276851,0.0002184432,0.00002568095,0.00008380688,0.000001329466,0.0006284499,0.9888187,0.0001914471,0.005746297,0.0005205607,0.003761702],"study_design_scores_gemma":[0.00009621464,0.00004196563,0.00002086269,0.000008405825,0.00001903316,5.764141e-7,0.00003157056,0.9940532,0.0006397152,0.004814052,0.0001619771,0.0001124001],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07356094,0.0003418667,0.9254529,0.0001444682,0.00008225534,0.000028816,0.000004321915,0.0001811342,0.0002033112],"genre_scores_gemma":[0.9872455,0.00007122214,0.01229974,0.0002420658,0.0001038355,0.000001333711,0.00001193025,0.00002003136,0.000004321897],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9136846,"threshold_uncertainty_score":0.4402563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01917956591427749,"score_gpt":0.2057867027624657,"score_spread":0.1866071368481882,"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."}}