{"id":"W2909296738","doi":"10.1109/access.2019.2892381","title":"Using Beamforming for Dense Frequency Reuse in 5G","year":2019,"lang":"en","type":"article","venue":"IEEE Access","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Beamforming; Computer science; Reuse; Smart antenna; Interference (communication); Antenna (radio); Signal-to-noise ratio (imaging); Electronic engineering; Telecommunications; Directional antenna; 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":[0.0002853546,0.0005459431,0.0001974565,0.0002759947,0.0002371943,0.0004596307,0.0002456057,0.0004119973,0.001786378],"category_scores_gemma":[0.0006432888,0.0002002405,0.0002992549,0.0004299515,0.0003950689,0.0006314471,0.0004147164,0.0002754427,0.0006293557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004181823,"about_ca_system_score_gemma":0.0004373117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001785166,"about_ca_topic_score_gemma":0.003834093,"domain_scores_codex":[0.9997312,0.00009672101,0.00001228405,0.00003421605,0.00009014529,0.00003538763],"domain_scores_gemma":[0.9998233,0.00007233109,0.00003247659,0.00003021954,0.00003386501,0.000007910492],"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":[0.0001412836,0.00007971963,0.003011553,0.0001699897,0.00008432358,0.0003385573,0.0001608185,0.4458109,0.1222372,0.1264376,0.003049207,0.2984789],"study_design_scores_gemma":[0.00005267539,0.000398033,0.002392753,0.00009242015,0.00004955507,0.0007038526,0.000110914,0.8874257,0.04114302,0.04444644,0.02311567,0.00006886598],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01389235,0.0002601005,0.9785028,0.0001879823,0.00003792227,0.00002799268,0.0000307839,0.0002974954,0.006762568],"genre_scores_gemma":[0.5830216,0.0007463921,0.4126988,0.0003013635,0.00006190738,0.00008509441,0.00007701655,0.00004506032,0.002962693],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001786378,"threshold_uncertainty_score":0.005976021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0857699566913249,"score_gpt":0.3232010036822541,"score_spread":0.2374310469909292,"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."}}