{"id":"W2944750697","doi":"10.1109/lwc.2019.2936854","title":"On Coverage Probability in Uplink NOMA With Instantaneous Signal Power-Based User Ranking","year":2019,"lang":"en","type":"preprint","venue":"IEEE Wireless Communications Letters","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Telecommunications link; Noma; Ranking (information retrieval); Base station; Decoding methods; Computer science; SIGNAL (programming language); Interference (communication); Coverage probability; Signal-to-noise ratio (imaging); Power (physics); Signal-to-interference-plus-noise ratio; Algorithm; Statistics; Telecommunications; Mathematics; Artificial intelligence; Physics","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":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0003554052,0.0007724895,0.000865059,0.0006762074,0.0002094667,0.0001494284,0.004853826,0.0005740575,0.00002200736],"category_scores_gemma":[0.00004197606,0.0008214336,0.0001731542,0.0006252193,0.000597458,0.000196101,0.000955909,0.003714908,0.00005767121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001256399,"about_ca_system_score_gemma":0.0001736994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006082896,"about_ca_topic_score_gemma":0.00026013,"domain_scores_codex":[0.9970131,0.0003114283,0.0009177796,0.0007207164,0.0004388234,0.0005981608],"domain_scores_gemma":[0.9885228,0.001265396,0.0003652697,0.009648266,0.0001238691,0.0000743839],"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":[0.00008413448,0.00022661,0.001021551,0.0002631467,0.00008690718,0.00001853678,0.000247192,0.9867952,0.00382187,0.001990072,0.0001265914,0.005318192],"study_design_scores_gemma":[0.004428667,0.0002849127,0.001889214,0.005393448,0.00008854146,0.00003236694,0.0002054959,0.9589148,0.01609949,0.005963431,0.002633081,0.004066511],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7470848,0.0005224982,0.2442012,0.002714406,0.000252084,0.001923478,0.0001011666,0.001843945,0.001356444],"genre_scores_gemma":[0.9762089,0.0006164447,0.02120097,0.0006161195,0.00001189869,0.0009000385,0.0002358001,0.000200991,0.000008865632],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2291241,"threshold_uncertainty_score":0.9994236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01845763824661669,"score_gpt":0.2360338137003642,"score_spread":0.2175761754537476,"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."}}