{"id":"W2943988096","doi":"10.1007/s11277-019-06459-y","title":"Estimation of Distribution Algorithm for Joint Resource Management in D2D Communication","year":2019,"lang":"en","type":"article","venue":"Wireless Personal Communications","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Mathematical optimization; Throughput; Greedy algorithm; Constraint (computer-aided design); Computational complexity theory; Resource allocation; Optimization problem; Interference (communication); Resource management (computing); Algorithm; Distributed computing; Wireless; Computer network; Mathematics; Telecommunications","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":[0.0002777537,0.0001153773,0.0001914305,0.0001123883,0.0000823517,0.00001457855,0.0003939974,0.0000709261,0.000007056155],"category_scores_gemma":[0.000008211539,0.0001403291,0.00005583861,0.00029372,0.00005598092,0.0001957681,0.0001052345,0.000142555,0.00001191153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002355355,"about_ca_system_score_gemma":0.00001040351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002195258,"about_ca_topic_score_gemma":0.00002417086,"domain_scores_codex":[0.9991472,0.00006966964,0.0004048705,0.0001214046,0.0001115883,0.0001452515],"domain_scores_gemma":[0.9987212,0.0001320097,0.00011267,0.0009345379,0.00007253981,0.00002698351],"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":[0.00001671348,0.0002024802,0.0001862697,0.0004694569,0.00009363115,1.786106e-7,0.002055755,0.3483325,0.001061825,0.02251098,0.0004812839,0.624589],"study_design_scores_gemma":[0.000533021,0.00001639337,0.0004743575,0.0001830231,0.00001497362,0.000001364679,0.0009589071,0.9951708,0.0004519343,0.0002938144,0.001770338,0.0001310333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01697867,0.0007310255,0.977199,0.0001953683,0.0000497327,0.001211809,0.0001634482,0.0001474034,0.003323578],"genre_scores_gemma":[0.878261,0.0003216968,0.1193324,0.000007995365,0.000005519594,0.0002789835,0.001671734,0.00002647208,0.00009413687],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8612823,"threshold_uncertainty_score":0.5722455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01742084655143082,"score_gpt":0.2559718155713314,"score_spread":0.2385509690199006,"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."}}