{"id":"W7127550824","doi":"","title":"Meta-Learning-Based Fronthaul Compression for Cloud Radio Access Networks","year":2025,"lang":"en","type":"article","venue":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Overhead (engineering); Gradient descent; Cloud computing; Radio access network; Convergence (economics); Remote radio head; Component (thermodynamics); Rate of convergence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003384416,0.0003245213,0.0005810065,0.0009258903,0.0002125649,0.00008282713,0.001004481,0.00037553,0.00005706199],"category_scores_gemma":[0.000610735,0.0003210979,0.0001474015,0.001296047,0.0001928521,0.0008565618,0.0002588518,0.0004202022,0.000005239043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001414002,"about_ca_system_score_gemma":0.00008999415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003192757,"about_ca_topic_score_gemma":0.00002740897,"domain_scores_codex":[0.9982111,0.00003207523,0.000725243,0.000493105,0.0001599316,0.0003784763],"domain_scores_gemma":[0.9979744,0.00008294901,0.0003154912,0.001061114,0.0004899332,0.0000760878],"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":[0.00003071095,0.00007183307,0.0004785243,0.0002736889,0.0003966917,8.263075e-7,0.000004455412,0.9548347,0.0002515823,0.008458766,0.031489,0.003709247],"study_design_scores_gemma":[0.0008814885,0.00002370206,0.00005080456,0.0001244124,0.0003333156,7.605107e-7,0.00001224087,0.7532889,0.006885393,0.00009653129,0.2380602,0.0002423515],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0005678475,0.001804331,0.990585,0.001191417,0.00121975,0.001176578,0.0002754071,0.001665884,0.001513749],"genre_scores_gemma":[0.8444127,0.0001817789,0.1437834,0.0002148166,0.0001937881,0.00219491,0.007613608,0.0001115221,0.001293416],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8468016,"threshold_uncertainty_score":0.9999241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02849232166477557,"score_gpt":0.2825977840922339,"score_spread":0.2541054624274583,"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."}}