{"id":"W2539255136","doi":"10.1109/pimrc.2014.7136378","title":"Partial mobile data offloading with load balancing in heterogeneous cellular networks using Software-Defined Networking","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Cellular traffic; Cellular network; Quality of service; Load balancing (electrical power); Computer network; Software-defined networking; Distributed computing; Small cell; Mobile computing; Resource allocation","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003865997,0.0002678301,0.0003356581,0.00008036082,0.00008283946,0.00006897545,0.0002892516,0.0001228017,0.00001816512],"category_scores_gemma":[0.00003016436,0.0002631309,0.00002453485,0.0003435476,0.00002117353,0.0003724695,0.0001275132,0.0002003228,0.000006681392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002353792,"about_ca_system_score_gemma":0.00002318888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009578803,"about_ca_topic_score_gemma":0.0002628881,"domain_scores_codex":[0.9983659,0.00005383426,0.0004241799,0.0004253743,0.0001737583,0.000556889],"domain_scores_gemma":[0.9989558,0.0001054138,0.00007866324,0.000732283,0.00003783781,0.00008993516],"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":[0.0000105234,0.0000072107,0.003045855,0.00003585278,0.00001911981,0.00001268498,0.00005574205,0.9926739,0.001084467,0.000006302815,0.00002274131,0.003025604],"study_design_scores_gemma":[0.0004480082,0.00002700057,0.000007107719,0.0001908664,0.00001888315,0.00002406639,0.00001965733,0.9970345,0.001035652,0.000006210605,0.000855189,0.0003328224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05841835,0.0007213908,0.9392545,0.000001104619,0.0005285552,0.0003142024,0.00000209523,0.0005390744,0.000220756],"genre_scores_gemma":[0.9250083,0.00002282365,0.0742377,0.0000199421,0.0005119315,0.00002213581,0.00005695333,0.0001059859,0.00001420327],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.86659,"threshold_uncertainty_score":0.9999821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01440565034532244,"score_gpt":0.2159879944517032,"score_spread":0.2015823441063807,"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."}}