{"id":"W2419144360","doi":"10.1109/wts.2016.7482052","title":"Resource management in OFDMA heterogeneous network","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kensington Health","funders":"European Social Fund; National Technical University of Athens; European Commission","keywords":"Orthogonal frequency-division multiple access; Computer science; Channel state information; Resource allocation; Resource management (computing); Interference (communication); Frequency-division multiple access; Radio resource management; Heterogeneous network; Computer network; Orthogonal frequency-division multiplexing; Channel (broadcasting); Distributed computing; Telecommunications; Wireless network; Wireless","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":[0.00003735762,0.00008081646,0.00007310106,0.00003835377,0.00001272774,0.000005570561,0.00007370472,0.00003251006,0.0001214731],"category_scores_gemma":[0.000001002096,0.00006114693,0.00001556492,0.0001561105,0.000008228665,0.00005553577,0.00002061006,0.0000278294,0.00004097646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005793892,"about_ca_system_score_gemma":6.150983e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.17159e-7,"about_ca_topic_score_gemma":0.00001352049,"domain_scores_codex":[0.9994715,0.000009037019,0.0001252275,0.0001078928,0.00006076747,0.0002255528],"domain_scores_gemma":[0.9997901,0.00002241292,0.000009435918,0.0001447396,0.000004252457,0.00002905777],"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":[0.000003376161,0.000003047026,0.0003456344,0.000005339205,0.00001031767,0.000009186775,0.000005564031,0.9040442,0.00004047652,0.0007925201,0.001943008,0.0927974],"study_design_scores_gemma":[0.001676132,0.00002874126,0.002316767,0.0003396068,0.0000168654,0.000008808736,0.00002459718,0.813834,0.002577284,0.002621299,0.1758022,0.0007537152],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02450085,0.0007064086,0.8982212,0.0001962094,0.0002628283,0.0002950088,0.000001251065,0.0008399806,0.07497629],"genre_scores_gemma":[0.9834861,0.0008306564,0.01366757,0.00008283852,0.0001294334,0.0000475296,0.000001927241,0.00004213234,0.001711826],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9589852,"threshold_uncertainty_score":0.24935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004552831958689042,"score_gpt":0.1827461767716473,"score_spread":0.1781933448129582,"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."}}