{"id":"W3017992635","doi":"10.1007/s41745-020-00162-9","title":"Non-orthogonal Multiple Access: An Enabler for Massive Connectivity","year":2020,"lang":"en","type":"article","venue":"Journal of the Indian Institute of Science","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Orthogonality; Noma; Distributed computing; Scheme (mathematics); Computer network; Telecommunications link","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002745875,0.00007769414,0.0001601773,0.0001235026,0.000188892,0.00004657744,0.002149441,0.00003948594,0.000002651326],"category_scores_gemma":[0.0007873841,0.00005633565,0.00006560549,0.0005322678,0.0009202792,0.002012467,0.0002107243,0.0002383084,5.837763e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007435039,"about_ca_system_score_gemma":0.0002090725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002717798,"about_ca_topic_score_gemma":0.00001355211,"domain_scores_codex":[0.9992402,0.000006265055,0.0002656834,0.00008615971,0.0002498928,0.0001517544],"domain_scores_gemma":[0.9990788,0.00005826065,0.0002690848,0.0002881055,0.0002214685,0.00008427403],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002818829,0.00004215342,0.004822894,0.00008636316,0.00002829986,0.000005480837,0.001538625,0.7914657,0.1862466,0.001554096,0.0002966593,0.01388496],"study_design_scores_gemma":[0.001023833,0.0002348857,0.02932349,0.0001966822,0.00001546292,0.00004008817,0.001165717,0.08043985,0.8769519,0.003993267,0.006337873,0.0002769568],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9465479,0.00005058603,0.0512027,0.001403907,0.0004886964,0.0001546635,0.00001192015,0.00003434404,0.0001053289],"genre_scores_gemma":[0.9865046,0.00003356181,0.01330555,0.00009620678,0.00004699729,0.000004326843,2.065971e-7,0.000006741647,0.00000182621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7110258,"threshold_uncertainty_score":0.3994231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03772430456287314,"score_gpt":0.2824070357070252,"score_spread":0.2446827311441521,"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."}}