{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001756639,0.0009691252,0.001489822,0.0007407802,0.0005917924,0.001079306,0.0012641,0.001063534,0.002581388],"category_scores_gemma":[0.005716643,0.0006760909,0.0006817163,0.001263912,0.0007365061,0.001719874,0.001727601,0.001308946,0.0006377122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001019593,"about_ca_system_score_gemma":0.002603204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006058915,"about_ca_topic_score_gemma":0.004228544,"domain_scores_codex":[0.9991556,0.0003215369,0.00004074937,0.0001505272,0.0002165078,0.0001150229],"domain_scores_gemma":[0.9978613,0.001438535,0.0001199411,0.0001247378,0.000383865,0.00007159255],"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":[0.0002061746,0.00007144938,0.0007810096,0.00009443496,0.00005973567,0.00003533539,0.00006279546,0.860435,0.001862461,0.01620587,0.003014645,0.1171711],"study_design_scores_gemma":[0.000009641387,0.0000128874,0.0000681642,0.000003367195,0.000003741255,0.000009275233,0.000004997166,0.9970182,0.0003227053,0.002327168,0.0002155418,0.000004186872],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003172267,0.0001111652,0.9960139,0.00009339388,0.00002145948,0.00002200883,0.00002982418,0.0001220572,0.0004140048],"genre_scores_gemma":[0.4008278,0.0006108366,0.5927876,0.0002137927,0.0001337074,0.0004342323,0.0004478809,0.0001445075,0.00439966],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006058915,"threshold_uncertainty_score":0.01204729,"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."}}