{"id":"W180077639","doi":"10.1007/978-1-4757-3333-4_5","title":"Evaluation of Penalty Functions for Optimal Control","year":2001,"lang":"en","type":"book-chapter","venue":"Applied optimization","topic":"Aerospace Engineering and Control Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Mashhad University of Medical Sciences","keywords":"Penalty method; Optimal control; Quadratic equation; Function (biology); Mathematical optimization; Mathematics; Bellman equation; State (computer science); Series (stratigraphy); Value (mathematics); Control theory (sociology); Control (management); Computer science; Algorithm; Statistics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004962406,0.0002799639,0.0003980906,0.0001287999,0.00004861459,0.00001915791,0.00008855293,0.0003261662,0.0002044265],"category_scores_gemma":[0.00001902365,0.0003150076,0.0001254441,0.0000407215,0.00001928917,0.00004695758,0.000005975623,0.0001365998,0.00002039374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001863154,"about_ca_system_score_gemma":0.00005031268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001706683,"about_ca_topic_score_gemma":0.000002338745,"domain_scores_codex":[0.9987722,0.000007183532,0.0003896946,0.0002117168,0.0004454858,0.0001737307],"domain_scores_gemma":[0.9991016,0.00006006557,0.0001430066,0.0002579283,0.0003865742,0.00005075822],"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":[0.00001930647,0.000005212816,2.969936e-7,0.00006894745,0.0002279123,7.936055e-8,0.00002188353,0.9859639,0.0001167453,0.007810878,0.001360679,0.00440413],"study_design_scores_gemma":[0.00159889,0.0000309243,0.000001672163,0.00005431121,0.0007670006,0.000001584961,0.00001131107,0.9852519,0.00002551201,0.0002294825,0.01175305,0.0002743767],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000006235305,0.0004852158,0.7173895,0.000007491967,0.0003263663,0.001063123,0.00007926829,0.0002010665,0.2804418],"genre_scores_gemma":[0.8945059,0.0002695168,0.01500953,0.00002646962,0.001596723,0.002013529,0.001803162,0.0006168783,0.08415827],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8944997,"threshold_uncertainty_score":0.9999302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0137973281288541,"score_gpt":0.1993677330224825,"score_spread":0.1855704048936284,"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."}}