{"id":"W3200312993","doi":"10.1109/jiot.2021.3112881","title":"Energy-Efficient RIS-Assisted Satellites for IoT Networks","year":2021,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Telecommunications link; Computer science; Computer network; Transmission (telecommunications); Beamforming; Path loss; Internet of Things; Satellite; Broadcasting (networking); Path (computing); Telecommunications; Wireless; Embedded system; Engineering; Aerospace engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006394361,0.0001849046,0.0001389724,0.000126563,0.0001613495,0.0002946965,0.0002352257,0.0001588242,0.00137123],"category_scores_gemma":[0.0001365683,0.00006588519,0.0001231084,0.0002312056,0.0001837035,0.000305243,0.0002155027,0.0001801095,0.0003750519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002121463,"about_ca_system_score_gemma":0.0001315747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003362077,"about_ca_topic_score_gemma":0.001041199,"domain_scores_codex":[0.9999568,0.000008865341,0.000001569227,0.000005471872,0.00001906508,0.000008249264],"domain_scores_gemma":[0.999944,0.00001645012,0.00001008682,0.00001005443,0.00001450467,0.000004873659],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003670601,0.00007188963,0.00320027,0.0002476366,0.00005371391,0.000413952,0.0001868371,0.2364828,0.4924678,0.05498259,0.00541838,0.2061071],"study_design_scores_gemma":[0.00003697135,0.0005470546,0.002904603,0.00003312377,0.00004969481,0.000434564,0.0001978399,0.7931309,0.150619,0.01430233,0.03771523,0.00002858183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3534274,0.002315543,0.5851616,0.0005806705,0.0001590218,0.00007161307,0.0001710186,0.001395862,0.0567173],"genre_scores_gemma":[0.9469033,0.0004832539,0.0492105,0.00005220237,0.00002174579,0.00002367256,0.00009906751,0.0000234194,0.003182749],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00137123,"threshold_uncertainty_score":0.004587233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01648446858393893,"score_gpt":0.240892028361935,"score_spread":0.2244075597779961,"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."}}