{"id":"W4200596779","doi":"10.3390/electronics10243061","title":"Resource Allocation in NOMA-Assisted Ambient Backscatter Communication System","year":2021,"lang":"en","type":"article","venue":"Electronics","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Decoding methods; Backscatter (email); Benchmark (surveying); Noma; Computer science; Reflection (computer programming); Mathematical optimization; Resource allocation; Optimization problem; Computational complexity theory; Algorithm; Mathematics; Telecommunications; Wireless; Telecommunications link; Computer network; Geography","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":[0.0001400925,0.0001193307,0.0001507196,0.00009841484,0.00006327788,0.00002837752,0.0004042735,0.00011506,0.000009255114],"category_scores_gemma":[0.00003412352,0.0001447806,0.00003220021,0.0005054391,0.00003145664,0.0001131329,0.0001116966,0.000401243,0.00004011306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007553477,"about_ca_system_score_gemma":0.00003891325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002460315,"about_ca_topic_score_gemma":0.0002205603,"domain_scores_codex":[0.9991093,0.00008287914,0.0002830927,0.0001505588,0.0001114589,0.0002626822],"domain_scores_gemma":[0.9986357,0.00007283794,0.00004873468,0.001161148,0.00005978827,0.00002180382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003221382,0.0003465073,0.001966872,0.0005597718,0.0001765358,0.00002624083,0.001382753,0.3065313,0.2269826,0.1396969,0.005787764,0.3165106],"study_design_scores_gemma":[0.001349971,0.00005615283,0.01102969,0.0004454353,0.00002512529,0.00009979847,0.003251033,0.1411183,0.455896,0.001388276,0.3844253,0.0009148833],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.773889,0.1124444,0.08055805,0.005562309,0.0001840953,0.0007503139,0.000009472749,0.005354848,0.02124749],"genre_scores_gemma":[0.9931487,0.002095084,0.004375078,0.00004756617,0.000006941098,0.00008226682,0.000101113,0.00003387194,0.0001093296],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3786376,"threshold_uncertainty_score":0.5903981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009666667565935679,"score_gpt":0.2206375634991212,"score_spread":0.2109708959331855,"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."}}