{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004651514,0.0004320248,0.0006773159,0.0004667553,0.0003425776,0.0006575293,0.0009948802,0.0007696868,0.004029503],"category_scores_gemma":[0.001468518,0.0004405698,0.0007245422,0.0002620891,0.0009967388,0.0008680286,0.00121743,0.001325763,0.0005795393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00100629,"about_ca_system_score_gemma":0.0009482481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005949738,"about_ca_topic_score_gemma":0.004869739,"domain_scores_codex":[0.9997315,0.00007527148,0.00001033277,0.00004149621,0.000118081,0.00002331186],"domain_scores_gemma":[0.9995626,0.000186331,0.00004282226,0.00008573339,0.00008977672,0.00003285326],"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":[0.00001763187,0.0000148222,0.0001567013,0.00001842883,0.00001289973,0.00001727297,0.00002460666,0.962814,0.002011227,0.02860085,0.0003260314,0.00598564],"study_design_scores_gemma":[9.345825e-7,0.000001438164,0.000009362905,6.434432e-7,3.901191e-7,0.000001296476,8.181199e-7,0.997466,0.0001610928,0.002199596,0.0001575923,9.377796e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01851851,0.00005565022,0.9788021,0.0001818351,0.00002734915,0.00002580673,0.00009892457,0.000288981,0.002000808],"genre_scores_gemma":[0.7189814,0.0001933357,0.2712654,0.0001577906,0.00003767119,0.000290705,0.0005182241,0.0004145979,0.008140822],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005949738,"threshold_uncertainty_score":0.01348007,"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."}}