{"id":"W7082659851","doi":"10.1109/tnsm.2025.3612425","title":"Spectrum and RAN Sharing: How to Avoid Cross-Subsidization While Taking Full Advantage of Massive MU-MIMO?","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Network and Service Management","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Isolation (microbiology); Telecommunications link; A priori and a posteriori; Operator (biology); Spectral efficiency; Base station; Resource management (computing); Resource (disambiguation); Exploit","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":[0.0002021483,0.0001545538,0.0001672146,0.0001096529,0.000293712,0.000173994,0.0003252959,0.00005628764,0.00002114087],"category_scores_gemma":[0.000001954085,0.0001586533,0.00003442114,0.0006947517,0.00002274647,0.0001717741,0.00003939253,0.0001165641,0.000002551876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002056547,"about_ca_system_score_gemma":0.00000875368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001389521,"about_ca_topic_score_gemma":0.0001361803,"domain_scores_codex":[0.9989405,0.00002583859,0.0001873677,0.0004604536,0.0001288161,0.0002569985],"domain_scores_gemma":[0.9993649,0.0000488192,0.00009033339,0.0003704547,0.00005926099,0.00006624014],"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":[0.000200087,0.0002149189,0.001509444,0.001885537,0.0003133967,0.00003982579,0.001749067,0.9091656,0.001576939,0.03417083,0.0004876328,0.04868677],"study_design_scores_gemma":[0.004139146,0.000534643,0.02639479,0.001803245,0.0003157789,0.00002343805,0.002656965,0.8800957,0.01827581,0.0176324,0.04664848,0.001479643],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02443468,0.00005507354,0.9543259,0.009506806,0.0003395394,0.0003282548,0.000002380646,0.00007829042,0.01092906],"genre_scores_gemma":[0.9925127,0.000154313,0.004734938,0.001007818,0.00002964647,0.00003451768,0.000002107444,0.000003431194,0.00152051],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.968078,"threshold_uncertainty_score":0.6469694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01262639542516468,"score_gpt":0.2350527402677723,"score_spread":0.2224263448426076,"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."}}