{"id":"W4387031627","doi":"10.1111/cgf.14963","title":"OptCtrlPoints: Finding the Optimal Control Points for Biharmonic 3D Shape Deformation","year":2023,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Kootenay Association for Science & Technology","funders":"Institute for Information and Communications Technology Promotion; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Research Foundation of Korea; Ministry of Science and ICT, South Korea; Ministry of Trade, Industry and Energy; Association of Research Libraries","keywords":"Biharmonic equation; Computation; Computer science; Set (abstract data type); Control point; Reduction (mathematics); Usability; Point (geometry); Matrix (chemical analysis); Control (management); Algorithm; Mathematical optimization; Artificial neural network; Artificial intelligence; Mathematics; Geometry","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":[],"consensus_categories":[],"category_scores_codex":[0.0004146488,0.0001742312,0.0001942979,0.0002931376,0.0002858952,0.0001155037,0.0002905366,0.00008392807,0.000008623836],"category_scores_gemma":[0.00001345031,0.0001365942,0.0002366428,0.000590153,0.00002878796,0.0001690595,0.00005333691,0.0001815517,0.00007615434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002686156,"about_ca_system_score_gemma":0.000009942608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001828267,"about_ca_topic_score_gemma":0.000004197927,"domain_scores_codex":[0.9989008,0.00002054392,0.0002843704,0.0001754603,0.0001646225,0.000454188],"domain_scores_gemma":[0.9994249,0.0001592844,0.00004360174,0.0002485903,0.00006496486,0.0000586009],"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":[0.00001485738,0.00001658396,0.000533817,0.0001006818,0.000399386,0.000004286897,0.0004209674,0.9519172,0.00007226165,0.006052722,0.01510057,0.0253666],"study_design_scores_gemma":[0.0004805069,0.00003152311,0.0002120253,0.00003178231,0.00005293313,0.000004175794,0.0000459882,0.9959443,0.00005196693,0.001349934,0.001622305,0.0001725785],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1012993,0.0001352996,0.8958604,0.001233041,0.0005247777,0.0002396282,0.00003548573,0.0006346473,0.00003745791],"genre_scores_gemma":[0.9964144,0.00008952885,0.002686946,0.000430369,0.00017315,0.0000657202,0.00008098233,0.00004037692,0.0000185413],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8951151,"threshold_uncertainty_score":0.5570151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01768079286010588,"score_gpt":0.2301748111719105,"score_spread":0.2124940183118047,"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."}}