{"id":"W7105919186","doi":"10.23952/jano.7.2025.3.09","title":"A discontinuous Galerkin method for optimal control of the obstacle problem","year":2025,"lang":"","type":"article","venue":"Journal of Applied and Numerical Optimization","topic":"Spacecraft Dynamics and Control","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Air Force Office of Scientific Research; Office of Naval Research; National Science Foundation","keywords":"Optimal control; Obstacle problem; Discontinuous Galerkin method; Control theory (sociology); Obstacle; Control (management)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007986492,0.0005864406,0.0006365773,0.0004364251,0.0002524487,0.0005303788,0.0006054202,0.0006473282,0.001190498],"category_scores_gemma":[0.001062741,0.000235617,0.0004342661,0.0002321468,0.0009269349,0.0005356118,0.001092294,0.001233389,0.0002204472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003498931,"about_ca_system_score_gemma":0.0006856495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007476406,"about_ca_topic_score_gemma":0.0005706004,"domain_scores_codex":[0.9996778,0.0001223573,0.000008657311,0.00003223528,0.0001377274,0.00002112912],"domain_scores_gemma":[0.9996953,0.0001853368,0.00002743816,0.00002062409,0.00004675375,0.00002466223],"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":[0.0001384061,0.00007496504,0.000370275,0.0003553529,0.00004128139,0.0001082959,0.0001435225,0.7303237,0.02135641,0.1808109,0.001414136,0.06486273],"study_design_scores_gemma":[0.000008028651,0.00003228987,0.00005147937,0.000009513749,0.000003077806,0.0000159621,0.000004249127,0.9873043,0.000891355,0.009625817,0.002047628,0.000006272141],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004020784,0.0001945929,0.9943535,0.00007476853,0.00003271813,0.00001300416,0.00001232256,0.00003686104,0.001261478],"genre_scores_gemma":[0.4532661,0.0007749334,0.5377674,0.000167891,0.000118364,0.0002486217,0.0001123579,0.0001496157,0.007394748],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001190498,"threshold_uncertainty_score":0.004223704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002789678525770843,"score_gpt":0.2148386842803363,"score_spread":0.2120490057545654,"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."}}