{"id":"W4400233696","doi":"10.1109/iscas58744.2024.10558578","title":"Reinforcement-Learning-Based Successive Approximation Algorithm","year":2024,"lang":"en","type":"article","venue":"","topic":"Elevator Systems and Control","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Newfoundland and Labrador; Canada Foundation for Innovation","keywords":"Reinforcement learning; Computer science; Reinforcement; Approximation algorithm; Artificial intelligence; Algorithm; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001105158,0.0007950576,0.00146924,0.0004843702,0.0003557142,0.0006886701,0.001375643,0.001015509,0.002499033],"category_scores_gemma":[0.002619068,0.0003339585,0.0005530384,0.0004282291,0.0007587756,0.0004991543,0.0007545412,0.001384376,0.0004112367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007059308,"about_ca_system_score_gemma":0.00129749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00615214,"about_ca_topic_score_gemma":0.004097313,"domain_scores_codex":[0.9994839,0.0001422684,0.00003120558,0.00010114,0.0001669228,0.00007453219],"domain_scores_gemma":[0.998889,0.0006856616,0.00009572072,0.00004756766,0.0002287031,0.00005332388],"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":[0.00008156155,0.00007666223,0.0006512717,0.00008409444,0.00005953086,0.00006410179,0.00006799778,0.8932841,0.001652463,0.007803058,0.0008834727,0.09529169],"study_design_scores_gemma":[0.00001024391,0.00003040532,0.00003003438,0.000002952587,0.00000410852,0.000008844419,0.000002015924,0.998827,0.0001757353,0.0007010943,0.0002052055,0.000002339447],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01205909,0.0003891181,0.9839077,0.000124179,0.00006715402,0.00004782787,0.00001385365,0.0004028006,0.002988284],"genre_scores_gemma":[0.769783,0.0003489372,0.2245022,0.000222446,0.00008266444,0.0002564025,0.00008770094,0.00006012739,0.004656529],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00615214,"threshold_uncertainty_score":0.01223266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004133488390646299,"score_gpt":0.1976809027307863,"score_spread":0.19354741434014,"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."}}