{"id":"W2989693566","doi":"10.1109/pimrc.2019.8904401","title":"Resource Allocation in Moving Small Cell Network using Deep Learning based Interference Determination","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Gnowit (Canada)","funders":"","keywords":"Computer science; Quality of service; Resource allocation; Interference (communication); Software deployment; Cellular network; Computer network; Graph; Distributed computing","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":[0.0001958107,0.000119919,0.0001231538,0.0001238482,0.00003027431,0.00003391402,0.00008682015,0.00008101517,0.00004330405],"category_scores_gemma":[0.00002932347,0.0001399875,0.0000195439,0.0002642942,0.000004909011,0.0002207653,0.00002054141,0.0001636136,0.00002430181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002048024,"about_ca_system_score_gemma":0.00000919605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002227497,"about_ca_topic_score_gemma":0.0001648261,"domain_scores_codex":[0.9992465,0.00005445238,0.000251075,0.0001723035,0.00006206024,0.0002136332],"domain_scores_gemma":[0.9996455,0.00008455484,0.00006001554,0.0001429674,0.00003899889,0.00002792639],"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":[0.000003541934,0.000003879506,0.005215473,0.00007115105,9.76936e-7,6.206802e-7,0.0001621146,0.982336,0.008602046,0.00001556518,0.000001532062,0.003587074],"study_design_scores_gemma":[0.000235882,0.00001551025,0.00030122,0.00014151,0.000003089012,9.91315e-7,0.0001739465,0.995393,0.003463144,0.00001033777,0.0001063488,0.0001549552],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1690207,0.00006629929,0.8269095,0.000002792646,0.000116243,0.0002067923,1.031246e-7,0.0001944143,0.003483198],"genre_scores_gemma":[0.92392,0.000003229747,0.07574487,0.00001501305,0.00003924562,0.00000884508,0.00001432989,0.00003659353,0.0002178231],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7548994,"threshold_uncertainty_score":0.5708525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.010030848879015,"score_gpt":0.2041020562148165,"score_spread":0.1940712073358015,"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."}}