{"id":"W4288617802","doi":"10.48550/arxiv.1901.10535","title":"Generalized Coordinated Multipoint (GCoMP)-Enabled NOMA: Outage,\\n Capacity, and Power Allocation","year":2019,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Noma; Computer science; Base station; Transmission (telecommunications); Enhanced Data Rates for GSM Evolution; Computer network; Power (physics); Expression (computer science); Outage probability; Telecommunications link; Cellular network; Throughput; Mathematical optimization; Wireless; Mathematics; Telecommunications; Fading; Channel (broadcasting)","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":[0.0006789853,0.001187637,0.000873287,0.0005775685,0.0007618244,0.001041312,0.001437036,0.0006446922,0.001099308],"category_scores_gemma":[0.002183992,0.0003161513,0.0004855313,0.001096845,0.0009360938,0.0009531875,0.001660684,0.0007956051,0.0003123959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001194665,"about_ca_system_score_gemma":0.001234383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004152431,"about_ca_topic_score_gemma":0.006508471,"domain_scores_codex":[0.9990479,0.0003248846,0.0000281775,0.0001480284,0.0002638297,0.0001870847],"domain_scores_gemma":[0.9987276,0.0004937098,0.0001925496,0.0002261776,0.0002825816,0.00007738992],"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":[0.0002569099,0.00008849918,0.001945922,0.0002982077,0.0001323179,0.0007991679,0.0002085396,0.8349088,0.02332075,0.03789458,0.004320277,0.09582605],"study_design_scores_gemma":[0.000009141086,0.00008314577,0.0004000184,0.00000969698,0.0000261777,0.0003000746,0.00003601807,0.9907991,0.003602098,0.003447051,0.001265163,0.00002244143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05627235,0.001621053,0.9324736,0.0002230731,0.0001499134,0.00009147535,0.0001519631,0.0005606068,0.008455986],"genre_scores_gemma":[0.9542516,0.0004936596,0.04358499,0.00006761301,0.00007138321,0.00007329629,0.00007598906,0.00002441138,0.001357008],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004152431,"threshold_uncertainty_score":0.008668005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05292886917356927,"score_gpt":0.1841438490882472,"score_spread":0.131214979914678,"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."}}