{"id":"W4386607324","doi":"10.1111/cgf.14927","title":"Advances in Data‐Driven Analysis and Synthesis of 3D Indoor Scenes","year":2023,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Young Scientists Fund; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Focus (optics); Representation (politics); Artificial intelligence; Task (project management); Segmentation; Object (grammar); Metric (unit); Similarity (geometry); Deep learning; Human–computer interaction; Computer vision; Image (mathematics)","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":[0.0001683041,0.0001073813,0.0003079133,0.0009788469,0.00003231686,0.00002082869,0.0002622505,0.00005112606,0.000002148886],"category_scores_gemma":[0.00001186921,0.0001045129,0.00007183607,0.002148546,0.00003950837,0.0001683146,0.0001565093,0.00008240804,0.000002718909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004541865,"about_ca_system_score_gemma":0.000004410321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002489983,"about_ca_topic_score_gemma":0.00046531,"domain_scores_codex":[0.9992232,0.00001914217,0.0002270232,0.000217696,0.0001180011,0.0001949508],"domain_scores_gemma":[0.9994149,0.0001256729,0.00003006763,0.0003687035,0.00002295275,0.00003774269],"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":[0.000004022957,0.00003297512,0.2762289,0.0002045653,0.0007321131,0.00001241869,0.0001592405,0.5963069,0.00003339448,0.0004089323,0.0002995875,0.125577],"study_design_scores_gemma":[0.00007973376,0.000005178776,0.008114961,0.00004249869,0.0001673555,3.457003e-7,0.00002542319,0.9908966,0.00006819163,0.00030602,0.0001833016,0.0001104192],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5809295,0.002603658,0.4153699,0.0001990569,0.0001859031,0.00008801185,0.0001235492,0.0003830333,0.0001173328],"genre_scores_gemma":[0.9935514,0.003764621,0.002572142,0.00001460581,0.00002291351,0.000004643643,0.00005373634,0.00001326793,0.000002705305],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4127978,"threshold_uncertainty_score":0.4261913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01588301893734911,"score_gpt":0.2421406519730502,"score_spread":0.2262576330357011,"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."}}