{"id":"W4205367908","doi":"10.1109/jiot.2022.3142850","title":"A Joint Optimization Framework for IRS-Assisted Energy Self-Sustainable IoT Networks","year":2022,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Key Research and Development Projects of Shaanxi Province; National Natural Science Foundation of China","keywords":"Computer science; MIMO; Maximization; Wireless; Benchmark (surveying); Optimization problem; Maximum power transfer theorem; Energy harvesting; Internet of Things; Efficient energy use; Energy (signal processing); Mathematical optimization; Computer network; Channel (broadcasting); Distributed computing; Power (physics); Telecommunications; Algorithm; Electrical engineering; Engineering; Embedded system; Mathematics","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":[0.000326224,0.0001495143,0.0002426601,0.0002423862,0.0001951381,0.00006355419,0.0007271835,0.0001133013,0.00008018636],"category_scores_gemma":[0.0001188717,0.0001626733,0.0001304694,0.000255696,0.00003493628,0.0002133512,0.0001980364,0.0007948297,1.883502e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004777286,"about_ca_system_score_gemma":0.00002741709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001002749,"about_ca_topic_score_gemma":4.101754e-7,"domain_scores_codex":[0.9988539,0.00004941922,0.0004822417,0.0001149563,0.0001991095,0.0003003827],"domain_scores_gemma":[0.9989758,0.0001592192,0.000322152,0.000324293,0.0001711524,0.00004743296],"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":[0.00002734564,0.00004310892,0.000007239611,0.00003445532,0.0000996692,0.000006170429,0.0005090926,0.9787328,0.0002056439,0.0120916,0.003217048,0.005025854],"study_design_scores_gemma":[0.0002991954,0.0001353439,0.000005027585,0.00007143118,0.00001716518,0.0001199747,0.001017048,0.9684052,0.005423753,0.01322803,0.01110408,0.000173717],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003224716,0.001072405,0.9940429,0.0002293292,0.0005478319,0.0001117897,0.00000142369,0.0005004492,0.0002691127],"genre_scores_gemma":[0.7210773,0.0002536453,0.2782026,0.0001060288,0.00005276427,0.00007119653,0.000004795723,0.00003615776,0.0001955269],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7178526,"threshold_uncertainty_score":0.6633627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01307574981148411,"score_gpt":0.2286413003511031,"score_spread":0.215565550539619,"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."}}