{"id":"W4288781684","doi":"10.1109/twc.2022.3159187","title":"Joint User Scheduling, Phase Shift Control, and Beamforming Optimization in Intelligent Reflecting Surface-Aided Systems","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Beamforming; Scheduling (production processes); Mathematical optimization; Reinforcement learning; Optimization problem; Job shop scheduling; Telecommunications link; Artificial intelligence; Algorithm; Schedule; Computer network; Mathematics; Telecommunications","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004607774,0.0002745403,0.0003742523,0.0005018916,0.00103759,0.00008288234,0.0009378169,0.0001155439,0.00002600785],"category_scores_gemma":[0.00001705906,0.0003426966,0.00007486531,0.0008339552,0.0001705586,0.0003772654,0.00004298492,0.001316933,0.000005115156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005405527,"about_ca_system_score_gemma":0.00004095944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001177035,"about_ca_topic_score_gemma":0.0001841999,"domain_scores_codex":[0.9981083,0.000277393,0.0007568997,0.0002841047,0.000237302,0.0003360229],"domain_scores_gemma":[0.9973888,0.0004352228,0.000160325,0.001874998,0.00006602705,0.00007456107],"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":[0.00002066487,0.0002697434,0.00002962869,0.00003105974,0.00005013178,9.731014e-7,0.0006892649,0.987028,0.003698719,0.0009673485,0.000005193078,0.007209241],"study_design_scores_gemma":[0.001190034,0.00008354463,0.00001080608,0.00009158924,0.00002299929,0.00001351554,0.002634248,0.9901617,0.0045333,0.00009907981,0.000826318,0.0003329213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08507057,0.001827205,0.910368,0.0006111276,0.0002334665,0.000693,0.00007440264,0.001002587,0.0001195828],"genre_scores_gemma":[0.9622155,0.003633637,0.03320845,0.00003715568,0.000005478224,0.0007562781,0.00003196617,0.00007956834,0.00003195603],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8771596,"threshold_uncertainty_score":0.9999025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0437534966883957,"score_gpt":0.2985342795208342,"score_spread":0.2547807828324385,"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."}}