{"id":"W4403340330","doi":"10.1016/j.ifacol.2024.09.295","title":"Autonomous Control of Primary Separation Vessel using Reinforcement Learning","year":2024,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Imperial Oil (Canada); University of Alberta","funders":"","keywords":"Separation (statistics); Primary (astronomy); Reinforcement learning; Reinforcement; Control (management); Computer science; Materials science; Artificial intelligence; Composite material; Machine learning; Physics","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":[0.0001597539,0.0001497075,0.0002483272,0.0001139841,0.00004912884,0.00004738323,0.00006298833,0.00008501662,0.0000629792],"category_scores_gemma":[0.00001380222,0.0001452708,0.00009702325,0.0001673962,0.00001717666,0.0001491576,0.000008141857,0.0001918687,0.00004429886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001812362,"about_ca_system_score_gemma":0.00004329147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004591668,"about_ca_topic_score_gemma":0.000005856228,"domain_scores_codex":[0.9991232,0.0000278806,0.00033982,0.0001502506,0.0001738831,0.0001850223],"domain_scores_gemma":[0.9997215,0.00004636144,0.00003890217,0.0001149138,0.0000310799,0.0000472026],"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":[0.00001657212,0.000006481294,0.00002934784,0.0002251969,0.0001044001,0.000007064757,0.0003153532,0.7048347,0.2867081,0.00008402524,0.000006371224,0.007662388],"study_design_scores_gemma":[0.0005110381,0.0000618027,0.00005975711,0.0001070223,0.00004532155,0.00001761296,0.0001063042,0.9857231,0.002450293,0.000003305009,0.01076803,0.0001463711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5598519,0.008136196,0.4105324,0.0002110218,0.002982841,0.0008222139,0.00003067885,0.00202817,0.01540454],"genre_scores_gemma":[0.9965385,0.00003015333,0.002309087,0.00005596158,0.0002627217,0.00001525428,0.00002043855,0.00003523339,0.0007326382],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4366866,"threshold_uncertainty_score":0.592397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01029646919868433,"score_gpt":0.2437770607234928,"score_spread":0.2334805915248085,"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."}}