{"id":"W3187825182","doi":"10.1109/icc42927.2021.9500418","title":"Reliable Millimeter Wave Communication for IoT Devices","year":2021,"lang":"en","type":"article","venue":"","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Relay; Computer science; Stochastic geometry; Internet of Things; Base station; Energy consumption; Extremely high frequency; Computer network; Millimeter; Signal-to-noise ratio (imaging); Non-line-of-sight propagation; Real-time computing; Wireless; Telecommunications; Electrical engineering; Engineering; Embedded system; Physics","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":[0.0001048899,0.00007327736,0.0000887106,0.0000305248,0.000061058,0.00003830431,0.00005978236,0.00004594713,0.0002772785],"category_scores_gemma":[0.00001787061,0.00007130094,0.00004825751,0.000070437,0.000006206696,0.00005605218,0.00002465381,0.00005678201,0.0000377142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002148009,"about_ca_system_score_gemma":0.0000127438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006044159,"about_ca_topic_score_gemma":0.00006175798,"domain_scores_codex":[0.9995476,0.00001035263,0.0001591609,0.00009805149,0.00005777211,0.0001270741],"domain_scores_gemma":[0.9995346,0.00005121013,0.00001301498,0.0002613221,0.0001037064,0.00003611864],"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":[0.00003070354,0.0001509993,0.0004070906,0.001064189,0.0004525777,0.000007001857,0.00182179,0.1138853,0.719223,0.007015512,0.04815732,0.1077845],"study_design_scores_gemma":[0.0002397836,0.000009436729,0.00003800017,0.0000278227,0.00001766734,0.000004180077,0.0001157792,0.5493826,0.4051264,0.001198614,0.04369155,0.0001481372],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05602464,0.002120505,0.912815,0.0003863315,0.0001769454,0.0001762064,0.000007142159,0.0002857549,0.02800752],"genre_scores_gemma":[0.8100849,0.000202161,0.1872717,0.0004085136,0.00003033128,0.00003350301,0.0000604741,0.00002339642,0.001885027],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7540602,"threshold_uncertainty_score":0.3036005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04018286844435609,"score_gpt":0.2406373304770851,"score_spread":0.200454462032729,"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."}}