{"id":"W4323645991","doi":"10.1109/fnwf55208.2022.00130","title":"Vision-Assisted User Clustering for Robust mmWave-NOMA Systems","year":2022,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Ericsson (Canada)","funders":"King Fahd University of Petroleum and Minerals","keywords":"Computer science; Cluster analysis; Robustness (evolution); Channel state information; Base station; User equipment; Noma; Real-time computing; Data mining; Artificial intelligence; Telecommunications link; Wireless; Computer network; Telecommunications","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":[0.0006371618,0.001054353,0.000846842,0.000350345,0.0007281253,0.0007269349,0.001358146,0.001029134,0.00128053],"category_scores_gemma":[0.002268618,0.0003402115,0.0004458253,0.0003901353,0.000716245,0.0009621268,0.00120739,0.001082085,0.0006419561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001089622,"about_ca_system_score_gemma":0.001163018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007315448,"about_ca_topic_score_gemma":0.008511492,"domain_scores_codex":[0.9992381,0.0001722772,0.0000292923,0.0001782534,0.0002059207,0.0001761419],"domain_scores_gemma":[0.9992694,0.0002321233,0.0001046914,0.0001203729,0.0002096796,0.00006369637],"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":[0.0005140658,0.0001722247,0.001615338,0.0001583697,0.00007321769,0.0001651329,0.0002126529,0.7910828,0.03801996,0.007342927,0.003334461,0.1573089],"study_design_scores_gemma":[0.00001063233,0.0000788823,0.0003936194,0.0000080162,0.000008659514,0.00005463647,0.00003595329,0.9905171,0.006782634,0.001494239,0.000598486,0.00001730405],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04681224,0.0004946144,0.9466307,0.0003171978,0.00008074105,0.00007136499,0.00007336904,0.001448037,0.00407179],"genre_scores_gemma":[0.9117185,0.0001560131,0.08583887,0.0001917544,0.00003800172,0.00004846327,0.00008908948,0.0000394984,0.001879784],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007315448,"threshold_uncertainty_score":0.01454574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02661628674290676,"score_gpt":0.247480794289975,"score_spread":0.2208645075470682,"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."}}