{"id":"W4315605919","doi":"10.1109/globecom48099.2022.10001723","title":"Distributed RIS-Assisted FD Systems with Discrete Phase Shifts: A Reinforcement Learning Approach","year":2022,"lang":"en","type":"article","venue":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Beamforming; Reinforcement learning; Maximization; Computer science; Phase (matter); Wireless; Transmitter power output; Mathematical optimization; Optimization problem; Continuous phase modulation; Power (physics); Algorithm; Mathematics; Transmitter; Telecommunications; Artificial intelligence; Physics; Channel (broadcasting)","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","sts"],"consensus_categories":[],"category_scores_codex":[0.0004539479,0.0005082398,0.0005732204,0.0001574503,0.002727332,0.0003849482,0.004739051,0.0001232702,0.0001492823],"category_scores_gemma":[0.00006345304,0.0005514964,0.0001209724,0.002142976,0.0004207511,0.0003914603,0.002380645,0.001744505,0.00002539733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001499386,"about_ca_system_score_gemma":0.0001766012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003371442,"about_ca_topic_score_gemma":0.0001276636,"domain_scores_codex":[0.996661,0.0006097536,0.000834421,0.0005083729,0.0007180069,0.0006684558],"domain_scores_gemma":[0.9946361,0.0001707475,0.0003841344,0.004434815,0.0002080814,0.0001661562],"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":[0.00008397807,0.0003289259,0.0004050781,0.00007889057,0.0002633016,0.000007059302,0.00023521,0.95889,0.0003847828,0.02547619,0.003041227,0.01080533],"study_design_scores_gemma":[0.00191931,0.0003441373,0.0002499851,0.00007118558,0.00007970481,0.00007843048,0.01168264,0.8901863,0.00006799406,0.0003879932,0.09402901,0.0009033276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01811958,0.007789737,0.9305633,0.0009424298,0.0004166318,0.002058444,0.001992439,0.004839025,0.03327845],"genre_scores_gemma":[0.984459,0.001567947,0.007562939,0.00003783395,0.00001286376,0.002556777,0.003536278,0.00005775238,0.0002085983],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9663394,"threshold_uncertainty_score":0.9996936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03334916894112717,"score_gpt":0.2801202113228782,"score_spread":0.2467710423817511,"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."}}