{"id":"W4403675301","doi":"10.23919/softcom62040.2024.10721660","title":"GWO-Based User Clustering And Power Allocation For Downlink MIMO-NOMA Systems","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Agence Nationale de la Recherche","keywords":"Noma; Telecommunications link; Cluster analysis; Computer science; MIMO; Computer network; Artificial intelligence","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":[0.00007014302,0.00009922855,0.00009506095,0.0001051145,0.0000372378,0.00008288835,0.0001338899,0.00008203046,0.000007859951],"category_scores_gemma":[0.00002117245,0.00009237974,0.00002249325,0.0001086526,0.00002555771,0.0001537307,0.00003941579,0.00008676112,0.00001255432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005448428,"about_ca_system_score_gemma":0.000007164386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004914566,"about_ca_topic_score_gemma":0.00001048026,"domain_scores_codex":[0.9995455,0.000005498903,0.0001523288,0.0001255074,0.00004814765,0.0001230702],"domain_scores_gemma":[0.9994952,0.000134193,0.00001051668,0.0003129546,0.00002684584,0.00002028555],"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":[0.00001131417,0.00001703683,0.0001318289,0.001589197,0.00009586612,0.000002623628,0.0002124713,0.8733557,0.02692896,0.0471535,0.003557293,0.04694423],"study_design_scores_gemma":[0.0001246459,0.00001817374,0.00006625222,0.0001010235,0.000004635013,0.000002524959,0.0001808396,0.9527286,0.006510441,0.0001743508,0.03995081,0.0001377558],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01236201,0.004298775,0.9786151,0.0004022607,0.0002845934,0.000319974,0.000008079041,0.002776115,0.0009330709],"genre_scores_gemma":[0.9770597,0.0001241642,0.02231261,0.00001976431,0.0000146506,0.0001797423,0.00001299103,0.0000335583,0.0002427735],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9646977,"threshold_uncertainty_score":0.3767137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01335444136503625,"score_gpt":0.2448316897335709,"score_spread":0.2314772483685347,"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."}}