{"id":"W4404628857","doi":"10.1109/ciot63799.2024.10757057","title":"A Deep Dive into Congestion Control and Buffer Management for Fluctuation-Prone 5G-A/6G Links","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Research and Development","keywords":"Network congestion; Computer science; Congestion management; Control (management); Computer network; Power (physics); Artificial intelligence; Physics","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":[0.001659646,0.0006485611,0.0005908481,0.00054683,0.0009474407,0.001451168,0.001474905,0.0006778234,0.001209534],"category_scores_gemma":[0.004905872,0.0002527748,0.0003837025,0.0004872365,0.001094015,0.002154748,0.0007239038,0.00147541,0.0001270045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001712872,"about_ca_system_score_gemma":0.001439758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01133311,"about_ca_topic_score_gemma":0.009598934,"domain_scores_codex":[0.9991923,0.0002455493,0.00002582636,0.000101185,0.0002409529,0.0001941584],"domain_scores_gemma":[0.9983084,0.0008728825,0.0002307133,0.0001494119,0.0003178316,0.0001206235],"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":[0.0001714355,0.0001485248,0.004503905,0.0001501283,0.0000771057,0.0001877089,0.0002311915,0.8896065,0.01089596,0.03315214,0.003574576,0.0573009],"study_design_scores_gemma":[0.000005082602,0.00006025299,0.0003437758,0.00001214871,0.000009499709,0.00003373269,0.00004177597,0.9946791,0.001367444,0.0024824,0.0009513513,0.00001349383],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3022448,0.004769627,0.6764784,0.002855109,0.0005627562,0.0002164627,0.0001461128,0.001386888,0.01133977],"genre_scores_gemma":[0.9851388,0.0006273821,0.01335817,0.0001374435,0.00005963531,0.00002495452,0.00002858097,0.00004237081,0.0005826261],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01133311,"threshold_uncertainty_score":0.02253431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00511660457778474,"score_gpt":0.2213476087442581,"score_spread":0.2162310041664734,"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."}}