{"id":"W3107547765","doi":"10.1007/978-3-030-58452-8_10","title":"House-GAN: Relational Generative Adversarial Networks for Graph-Constrained House Layout Generation","year":2020,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":259,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Theoretical computer science; Adjacency list; Graph; Algorithm","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008115285,0.0007801712,0.0007652002,0.0005059065,0.0006935871,0.0007591862,0.001922715,0.0005291905,0.00002138436],"category_scores_gemma":[0.000243597,0.0007433959,0.0003565174,0.0006594531,0.0007195951,0.001007247,0.0005479179,0.0007939361,0.00002449513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002720245,"about_ca_system_score_gemma":0.0008109013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001292435,"about_ca_topic_score_gemma":0.0001131414,"domain_scores_codex":[0.9953207,0.0001081871,0.0007886562,0.002140484,0.0008844348,0.0007575705],"domain_scores_gemma":[0.9970322,0.0007405931,0.000495838,0.0009351885,0.0005081802,0.000288002],"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":[0.00002433553,0.00002224401,0.00001065949,0.000009260801,0.00005226486,0.00002605225,0.0004877945,0.8856007,0.0003772831,0.03271889,0.0007520529,0.07991846],"study_design_scores_gemma":[0.0007014365,0.0002784688,0.00001687938,0.00007968264,0.00003225552,0.0000174518,2.940351e-7,0.9643267,0.001258159,0.03054473,0.001953354,0.0007906227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000009943626,0.0003698204,0.9906914,0.00222051,0.004677593,0.001053208,0.00002874509,0.000407449,0.000541341],"genre_scores_gemma":[0.1929472,0.00005470231,0.7960577,0.003297251,0.007255566,0.00005395818,0.00004869513,0.0001328371,0.0001521592],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1946337,"threshold_uncertainty_score":0.9995017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02765445398485078,"score_gpt":0.2303174894395121,"score_spread":0.2026630354546613,"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."}}