{"id":"W3165253014","doi":"10.1111/cgf.142619","title":"Semantics‐Guided Latent Space Exploration for Shape Generation","year":2021,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Subspace topology; Artificial intelligence; Space (punctuation); Semantics (computer science); Set (abstract data type); Artificial neural network; Generative model; Shape analysis (program analysis); Parametric statistics; Linear subspace; Generative grammar; Machine learning; Pattern recognition (psychology); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008876294,0.0008910988,0.0004472679,0.0004661495,0.0002941385,0.0009323503,0.001383285,0.001013116,0.008562657],"category_scores_gemma":[0.00338093,0.0005001671,0.0008859653,0.0003185591,0.0009748399,0.001955955,0.002315074,0.001483542,0.001498845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005941059,"about_ca_system_score_gemma":0.0004729739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001082419,"about_ca_topic_score_gemma":0.002711775,"domain_scores_codex":[0.9993721,0.0002517191,0.0000208049,0.000135952,0.0001775345,0.00004195634],"domain_scores_gemma":[0.9990308,0.0005133935,0.00005543584,0.0002492757,0.000098979,0.00005216528],"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":[0.000460896,0.0002451422,0.00177494,0.0003484999,0.0001018895,0.0003704689,0.0007601329,0.5068317,0.06185592,0.07707484,0.008743263,0.3414323],"study_design_scores_gemma":[0.00001574396,0.00002912881,0.00008853906,0.00001437755,0.000005649344,0.00005636033,0.00002388805,0.9698508,0.007986544,0.01852121,0.00339702,0.00001084586],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008594951,0.00009484352,0.9869365,0.0001498286,0.00002006958,0.00003701131,0.0000903444,0.00203097,0.002045375],"genre_scores_gemma":[0.4820545,0.0002304414,0.5094265,0.0003211306,0.000028706,0.0002344319,0.0004340787,0.0008548488,0.00641521],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008562657,"threshold_uncertainty_score":0.02864492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04873321706315401,"score_gpt":0.2433817924681985,"score_spread":0.1946485754050445,"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."}}