{"id":"W4391021200","doi":"10.1109/cdc49753.2023.10383229","title":"Distributed Source Seeking Using A Bi-Level Distributed Model Predictive Control Algorithm","year":2023,"lang":"en","type":"article","venue":"","topic":"Extremum Seeking Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council","keywords":"Computer science; Model predictive control; SIGNAL (programming language); Process (computing); Control (management); Distributed computing; Algorithm; Control theory (sociology); Artificial intelligence","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":[0.0004121326,0.0004292718,0.0005659385,0.0002478936,0.0002024207,0.0001385349,0.0003238292,0.0002383591,0.00001517219],"category_scores_gemma":[0.0001160102,0.0004324921,0.0001814198,0.001011859,0.00005105843,0.0002714149,0.00008414399,0.0003339975,0.00009826096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004287188,"about_ca_system_score_gemma":0.00005536843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001313029,"about_ca_topic_score_gemma":0.00001956229,"domain_scores_codex":[0.9975147,0.00007309995,0.0005838627,0.0004417071,0.0004742825,0.0009123096],"domain_scores_gemma":[0.998834,0.0002300661,0.00009221615,0.0004716242,0.0001457995,0.0002262869],"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":[0.00001331045,0.0000156787,0.0005035299,0.00004138986,0.0002435237,0.00002267852,0.0001583162,0.9668113,0.02864907,0.00004194723,0.001996418,0.001502843],"study_design_scores_gemma":[0.001681753,0.00002066798,0.0006440203,0.00009354087,0.00009256835,0.00002097183,0.0002003151,0.9958546,0.0001341972,0.0001620989,0.0006293203,0.0004660068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00638392,0.0001076501,0.9845543,0.00006867918,0.0004597337,0.0005595157,0.003014953,0.004445428,0.0004058525],"genre_scores_gemma":[0.9955821,0.000007219372,0.003139765,0.00003707558,0.0002783411,0.00007534835,0.0004943372,0.0001408867,0.00024493],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9891981,"threshold_uncertainty_score":0.9998127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02461492896266504,"score_gpt":0.2295715197202731,"score_spread":0.2049565907576081,"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."}}