{"id":"W2166210478","doi":"10.1109/icc.2010.5501861","title":"Resource Allocation via Linear Programming for Multi-Source, Multi-Relay Wireless Networks","year":2010,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science; Relay; Resource allocation; Computer network; Linear programming; Wireless; Wireless network; Optimization problem; Resource management (computing); Mathematical optimization; Distributed computing; Telecommunications; Algorithm; Mathematics","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":[0.0006951187,0.0001898887,0.0001745174,0.00008640881,0.0005106148,0.0002125087,0.001261992,0.0001431724,0.00001407925],"category_scores_gemma":[0.00008414391,0.0001724786,0.00009454461,0.0004503931,0.00007297967,0.0003012847,0.0004216416,0.0004265474,0.00002207835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002461763,"about_ca_system_score_gemma":0.00003566636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001165978,"about_ca_topic_score_gemma":0.0004889386,"domain_scores_codex":[0.9986107,0.00009928691,0.0003304915,0.0004358417,0.0001452083,0.0003784827],"domain_scores_gemma":[0.9982421,0.0002126323,0.0001281306,0.0009893224,0.0002824142,0.0001453406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008424322,0.0002221424,0.0004104573,0.000007757203,0.0000201847,4.768065e-7,0.0007299026,0.003785845,0.003861592,0.01838925,0.0005713358,0.9719926],"study_design_scores_gemma":[0.0006169241,0.00003431537,0.0003109787,0.0000138436,0.000004474277,0.000004159535,0.00002132381,0.8597571,0.0007669716,0.00000394043,0.1382586,0.0002074131],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003388318,0.00009603937,0.9940026,0.0009202966,0.0003112614,0.0006555057,2.883513e-7,0.0004678737,0.0001577614],"genre_scores_gemma":[0.4197341,0.00003398674,0.5774499,0.0005184865,0.0001582269,0.0001338042,0.00001668873,0.00002124546,0.001933551],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9717852,"threshold_uncertainty_score":0.7033471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04836137260390069,"score_gpt":0.3089085232240967,"score_spread":0.260547150620196,"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."}}