{"id":"W2964994311","doi":"10.1111/cgf.13645","title":"Latent‐space Dynamics for Reduced Deformable Simulation","year":2019,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":85,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Adobe Systems","keywords":"Robustness (evolution); Computer science; Nonlinear system; Autoencoder; Function space; Dynamics (music); Space (punctuation); Algorithm; Artificial neural network; Applied mathematics; Artificial intelligence; Mathematics; Mathematical analysis","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":[0.00006361095,0.0001336796,0.000146778,0.00007174515,0.0001220052,0.00005718943,0.0001222392,0.00005280281,0.00004366457],"category_scores_gemma":[4.313588e-7,0.0001259555,0.0001642821,0.0001576299,0.00001774037,0.0001804249,0.00005269437,0.0001270206,0.00002917151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001576793,"about_ca_system_score_gemma":0.0000155617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001156643,"about_ca_topic_score_gemma":0.000002153223,"domain_scores_codex":[0.9992059,0.00001270287,0.0001667786,0.0002262159,0.00009307208,0.0002952873],"domain_scores_gemma":[0.9994988,0.00004708304,0.00008601478,0.0002204254,0.00008050756,0.00006714383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003934597,0.00005952523,0.01625509,0.00001794242,0.00005945245,1.083936e-7,0.00004344969,0.4486165,0.00004134427,0.5178677,0.003075192,0.01392429],"study_design_scores_gemma":[0.0004896358,0.00006741823,0.0002869045,0.00001366295,0.0000101559,4.34429e-7,0.00001578036,0.9755507,0.0001065723,0.01549641,0.007807869,0.0001544557],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2876152,0.00001150788,0.7094331,0.0004369852,0.001131918,0.0004158582,0.00001732492,0.00005555343,0.0008825439],"genre_scores_gemma":[0.9968383,0.000001707841,0.001587953,0.000145051,0.0002892657,0.0000164214,0.0001609109,0.00002148775,0.0009388527],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7092231,"threshold_uncertainty_score":0.5136315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01170195565740225,"score_gpt":0.2447553203645912,"score_spread":0.233053364707189,"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."}}