{"id":"W3043899286","doi":"10.1109/ojvt.2020.3031656","title":"Rate-Splitting Multiple Access: Unifying NOMA and SDMA in MISO VLC Channels","year":2020,"lang":"en","type":"preprint","venue":"IEEE Open Journal of Vehicular Technology","topic":"Optical Wireless Communication Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Khalifa University of Science, Technology and Research","keywords":"Visible light communication; Computer science; Space-division multiple access; Broadband; Noma; Wireless; Bandwidth (computing); Key (lock); Multiplexing; Electronic engineering; Computer network; Telecommunications; Telecommunications link; Engineering; Electrical engineering; Light-emitting diode","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00103971,0.0009574996,0.0007283034,0.0007566581,0.0006692548,0.001786258,0.0008683326,0.0009490941,0.0007380947],"category_scores_gemma":[0.002079983,0.0003469687,0.0005777326,0.000752438,0.001216896,0.001493125,0.001209568,0.001284832,0.0002462112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008274438,"about_ca_system_score_gemma":0.001027043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002747771,"about_ca_topic_score_gemma":0.003282295,"domain_scores_codex":[0.9992532,0.0002826001,0.00003024719,0.00008927313,0.0002051576,0.000139485],"domain_scores_gemma":[0.9988853,0.0005718311,0.0001617212,0.00009822497,0.0002070257,0.0000757972],"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":[0.0003204424,0.0001195124,0.003307832,0.0004141422,0.0001396394,0.001396864,0.0007553636,0.4792989,0.02651721,0.4004835,0.002285435,0.08496127],"study_design_scores_gemma":[0.00002090248,0.0001279656,0.0003403652,0.00005643627,0.00004140057,0.0003684834,0.0001224264,0.9452751,0.002459758,0.04575916,0.005373614,0.00005440809],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05350827,0.005378899,0.9226902,0.0008380131,0.0002796163,0.0001211509,0.0001115915,0.0001822894,0.01688987],"genre_scores_gemma":[0.9315682,0.003731338,0.06137266,0.0002616303,0.0003832871,0.00009707685,0.0000548706,0.00002503664,0.00250589],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002747771,"threshold_uncertainty_score":0.006003559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05718366490543839,"score_gpt":0.3083434123746915,"score_spread":0.2511597474692531,"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."}}