{"id":"W4389540777","doi":"10.17118/11143/21101","title":"Control of a modified double inverted pendulum using machine learningbased model predictive control","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Inverted pendulum; Model predictive control; Double inverted pendulum; Computer science; Control theory (sociology); Control (management); Control engineering; Artificial intelligence; Engineering; Physics; Nonlinear system","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":[0.0002185614,0.0002223437,0.0004628338,0.0002442707,0.00006128653,0.00001690252,0.0001392662,0.0001228656,0.00002432778],"category_scores_gemma":[0.00005079491,0.0002208393,0.00009253642,0.0004306943,0.00003209894,0.0002643764,0.00001704962,0.0001726877,0.00001567375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001093834,"about_ca_system_score_gemma":0.00003739718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001794517,"about_ca_topic_score_gemma":0.00002517435,"domain_scores_codex":[0.9986653,0.00004622098,0.0004651723,0.0002235464,0.0002501413,0.0003495589],"domain_scores_gemma":[0.9992917,0.00009508791,0.0001117199,0.0002630868,0.0001463632,0.00009210257],"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":[0.0002400964,0.00001227881,0.0002823107,0.00004854058,0.0001437284,0.000002509417,0.00008978289,0.9449003,0.05347801,0.0006850371,0.00003969888,0.00007774276],"study_design_scores_gemma":[0.009403567,0.00003810408,0.00004804877,0.00003047914,0.00007070354,0.000001825315,0.00004125944,0.9885845,0.001418855,0.000157933,0.000009308825,0.0001954137],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02531139,0.00007990941,0.9705223,0.00002988147,0.0001444992,0.000776852,0.00007872219,0.001166382,0.001890057],"genre_scores_gemma":[0.9975497,0.000006319,0.001921845,0.00003650438,0.00003938407,0.00007766436,0.00003715441,0.00007589118,0.0002556008],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9722382,"threshold_uncertainty_score":0.9005566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01935759032107678,"score_gpt":0.2319329031295822,"score_spread":0.2125753128085054,"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."}}