{"id":"W2479310799","doi":"10.1109/icc.2016.7511273","title":"Media-based MIMO: Outperforming known limits in wireless","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Overhead (engineering); Channel (broadcasting); Computer science; Fading; Transmission (telecommunications); Wireless; MIMO; Signal-to-noise ratio (imaging); Modulation (music); Limit (mathematics); Bit error rate; Embedding; Algorithm; Topology (electrical circuits); Telecommunications; Mathematics; Artificial intelligence; Physics; Combinatorics","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":[0.002081616,0.001230828,0.001080181,0.0007622027,0.0007342544,0.002492164,0.001321509,0.001391837,0.003057212],"category_scores_gemma":[0.009364747,0.000490325,0.0003471733,0.0009861966,0.001900634,0.00405356,0.002280243,0.001830664,0.001248766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008748552,"about_ca_system_score_gemma":0.0005625236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007241554,"about_ca_topic_score_gemma":0.0007551087,"domain_scores_codex":[0.9979306,0.0005370793,0.0000609089,0.0002324847,0.0009894269,0.000249457],"domain_scores_gemma":[0.9943469,0.004038405,0.0003243269,0.0006186779,0.0005220598,0.0001497028],"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":[0.0009855208,0.0002079769,0.003365392,0.0009935147,0.0001474755,0.0008528297,0.0005770279,0.3631455,0.0500542,0.3488645,0.006550335,0.2242557],"study_design_scores_gemma":[0.00002988281,0.0003514492,0.0005831521,0.0001618955,0.00005359499,0.0007440001,0.0001612702,0.8531986,0.02207666,0.1124578,0.01009822,0.00008343248],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06117335,0.01436905,0.873389,0.001487055,0.0005131136,0.00006030065,0.0001866851,0.001309235,0.04751221],"genre_scores_gemma":[0.9008683,0.007281475,0.08542284,0.0004887783,0.0007028931,0.00007990671,0.000124179,0.0001123468,0.004919408],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003057212,"threshold_uncertainty_score":0.0110088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01857489599508538,"score_gpt":0.2303071402612634,"score_spread":0.2117322442661781,"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."}}