{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009310361,0.001329786,0.0009273739,0.0004532769,0.0005614568,0.001166771,0.001386634,0.000891002,0.001510458],"category_scores_gemma":[0.00177198,0.0003722145,0.0004853186,0.0007705365,0.000876238,0.00130322,0.001796834,0.001201634,0.0005232872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000463922,"about_ca_system_score_gemma":0.001254755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001133776,"about_ca_topic_score_gemma":0.002526622,"domain_scores_codex":[0.9988633,0.0004164654,0.0000292673,0.0001964959,0.0003222218,0.0001722155],"domain_scores_gemma":[0.9991325,0.000351435,0.0001314826,0.0001246197,0.0001990312,0.0000609361],"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":[0.0002911758,0.0001513,0.0009960855,0.0003992522,0.0001477144,0.0007150708,0.0001899718,0.6545919,0.03479954,0.1566699,0.005089751,0.1459583],"study_design_scores_gemma":[0.000009176543,0.0001012457,0.0001182477,0.00001142183,0.00001541058,0.0001622743,0.00002441838,0.9852909,0.002422152,0.009464682,0.00236449,0.00001565165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007547303,0.000466296,0.9871022,0.0001720517,0.00009511826,0.00003219646,0.00004506371,0.0001182371,0.004421478],"genre_scores_gemma":[0.7392769,0.0008829866,0.2498124,0.0003408979,0.0002175609,0.0001848448,0.000122331,0.00003909829,0.009122793],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001510458,"threshold_uncertainty_score":0.005053043,"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."}}