{"id":"W2907187178","doi":"10.1109/lwc.2018.2865770","title":"Extending the ITU-R P.530 Deep-Fading Outage Probability Results to SIMO-MRC and MIMO-MRC Line-of-Sight Systems","year":2018,"lang":"en","type":"article","venue":"IEEE Wireless Communications Letters","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ultra Electronics (Canada); École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Maximal-ratio combining; Fading; Rayleigh fading; MIMO; Mathematics; Computer science; Signal-to-noise ratio (imaging); Algorithm; Topology (electrical circuits); Telecommunications; Statistics; Beamforming; Decoding methods; Combinatorics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007075748,0.0002665869,0.0003475034,0.0001826038,0.000440427,0.0001013702,0.001059618,0.0001041836,0.000001867935],"category_scores_gemma":[0.0001480067,0.0002375066,0.00006004474,0.0005654847,0.0003580986,0.0003171338,0.0002088325,0.0003045502,0.00002159955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001951146,"about_ca_system_score_gemma":0.00001564547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001428424,"about_ca_topic_score_gemma":0.0002580148,"domain_scores_codex":[0.9980794,0.0002581885,0.0007955197,0.0003236246,0.0001947948,0.0003485056],"domain_scores_gemma":[0.996395,0.0005796303,0.0002103405,0.002517057,0.0001897295,0.0001082801],"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":[0.00003580354,0.00005729728,0.0005687665,0.0002859005,0.0001186737,0.000001729178,0.006969954,0.831015,0.1542903,0.001624569,0.0010065,0.004025556],"study_design_scores_gemma":[0.0007543184,0.00006083596,0.0004656046,0.000687993,0.00006757625,0.00002404135,0.0008463992,0.9781374,0.01239526,0.0000774239,0.005836625,0.000646573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4085422,0.001168002,0.582476,0.002980243,0.001099391,0.001820872,0.00007534533,0.0005439185,0.001293983],"genre_scores_gemma":[0.9845706,0.0001741999,0.01458764,0.0001502006,0.0001830548,0.0002095707,0.00002486147,0.00006548829,0.00003441066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5760283,"threshold_uncertainty_score":0.9685239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02944313640049112,"score_gpt":0.2635828401594227,"score_spread":0.2341397037589316,"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."}}