{"id":"W4403678666","doi":"10.1109/atnt61688.2024.10719225","title":"Role of AI and Open RAN in 6G Networks: Performance Impact and Key Technologies","year":2024,"lang":"en","type":"article","venue":"","topic":"Wireless Body Area Networks","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Key (lock); Ran; Computer science; Telecommunications; Computer network; Computer security","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":[0.0001098566,0.00009709604,0.0001578489,0.00009127894,0.0000132644,0.00008257089,0.0001336329,0.00009068678,0.000013534],"category_scores_gemma":[0.000005112763,0.00007741311,0.00001135766,0.0002210553,0.00004524995,0.0002991883,0.0001562541,0.0001970097,0.000001330715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002089029,"about_ca_system_score_gemma":0.000007557929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004620354,"about_ca_topic_score_gemma":0.00009012504,"domain_scores_codex":[0.9995578,0.000004714884,0.0001225433,0.0001150526,0.00003712126,0.0001627576],"domain_scores_gemma":[0.9998115,0.00003875675,0.000005899546,0.0001187209,0.000005667364,0.00001942013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000294039,0.0000129272,0.08148035,0.000299077,0.00009266211,0.00001160149,0.0008100806,0.4179067,0.001698155,0.001816105,0.002213492,0.4936294],"study_design_scores_gemma":[0.0001398459,0.00003120558,0.01817247,0.000177144,0.000004291614,0.000008386054,0.0001883128,0.9794568,0.001060443,0.0003185423,0.0003398682,0.000102654],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.980978,0.01336943,0.000671412,0.0000604296,0.00004461763,0.0001597064,0.000001771793,0.000378334,0.004336366],"genre_scores_gemma":[0.9977266,0.001931988,0.0002566817,0.000004957436,0.00001546988,0.00001262185,0.000001504301,0.00001744912,0.00003268739],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5615501,"threshold_uncertainty_score":0.3156815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004788975240517342,"score_gpt":0.2227785652207116,"score_spread":0.2179895899801943,"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."}}