{"id":"W4206542241","doi":"10.1109/lcomm.2022.3140271","title":"NOMA Empowered Integrated Sensing and Communication","year":2022,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":227,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Noma; Computer science; Base station; Throughput; Beamforming; Single antenna interference cancellation; Power (physics); Mathematical optimization; Computer network; Wireless; Telecommunications; Telecommunications link; Channel (broadcasting); Mathematics","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":[0.0001552704,0.0001046296,0.0001068925,0.0001658425,0.0006056097,0.00004502227,0.0006854916,0.00003442809,0.00002519273],"category_scores_gemma":[0.00001987894,0.0001238731,0.00002743696,0.0003706243,0.0001782849,0.00009308509,0.0002919958,0.0003979256,0.000008660938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001272553,"about_ca_system_score_gemma":0.000008783031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007165279,"about_ca_topic_score_gemma":0.00004570555,"domain_scores_codex":[0.9993493,0.0001286922,0.0001973226,0.00009411635,0.00009329092,0.0001372663],"domain_scores_gemma":[0.9984221,0.0001078794,0.00003748319,0.001379724,0.00002911168,0.00002365832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004557816,0.0002283706,0.004351773,0.0001280206,0.0004672154,0.00001878279,0.01507539,0.1739508,0.400114,0.014781,0.186147,0.2046922],"study_design_scores_gemma":[0.001051984,0.00004786685,0.001623302,0.0000525437,0.00006153016,0.0001246694,0.006398231,0.615082,0.01376845,0.001086614,0.359786,0.0009167861],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9000841,0.003488953,0.07087538,0.0163193,0.0004947981,0.0005368112,0.00007240156,0.00320242,0.004925875],"genre_scores_gemma":[0.9900663,0.0003541417,0.008642829,0.0007404583,0.000005445574,0.00003765286,0.0001037281,0.00002667106,0.00002280438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4411312,"threshold_uncertainty_score":0.50514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01382482148692997,"score_gpt":0.2175281669731723,"score_spread":0.2037033454862423,"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."}}