{"id":"W4408258275","doi":"10.1109/ccwc62904.2025.10903818","title":"Deep Reinforcement Learning-Based Sector Carrier Assignment in CloudRAN","year":2025,"lang":"en","type":"article","venue":"","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ericsson (Canada)","funders":"","keywords":"Reinforcement learning; Computer science; Reinforcement; Artificial intelligence; Engineering; Structural engineering","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":[0.0005366361,0.0006415289,0.0008081421,0.0002489668,0.0003009981,0.0005490635,0.001103153,0.0008463347,0.001861239],"category_scores_gemma":[0.001378695,0.0003164789,0.000331527,0.0002766396,0.000593606,0.0006916852,0.0007508054,0.001024385,0.0002122016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001126247,"about_ca_system_score_gemma":0.001485345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01592934,"about_ca_topic_score_gemma":0.01545775,"domain_scores_codex":[0.9997588,0.00005273173,0.000008206432,0.00006019293,0.00003872659,0.00008135052],"domain_scores_gemma":[0.9995265,0.0002280354,0.00005946201,0.00003377456,0.00009457739,0.00005764823],"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":[0.00006606901,0.00004781518,0.0005471654,0.00002275465,0.00001311417,0.00005518025,0.00002282322,0.9713621,0.0007564303,0.001932723,0.0007688697,0.02440498],"study_design_scores_gemma":[0.000004954042,0.000007834729,0.0000313963,0.000001227291,0.000001556171,0.000003098085,0.000003238635,0.9991645,0.0001246038,0.0005782554,0.00007828437,9.936091e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1403671,0.0006228229,0.8496148,0.0007242726,0.0001101889,0.00007628457,0.0001072204,0.001351503,0.007025754],"genre_scores_gemma":[0.942947,0.00007554812,0.05401708,0.0002214832,0.00001762229,0.0000383741,0.00008786313,0.00005044353,0.002544594],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01592934,"threshold_uncertainty_score":0.03167325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01058803391763427,"score_gpt":0.2367496600596259,"score_spread":0.2261616261419916,"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."}}