{"id":"W2614864174","doi":"10.1109/tcomm.2017.2706261","title":"Performance Analysis of Multiple Association in Ultra-Dense Networks","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Telecommunications link; Base station; Backhaul (telecommunications); Computer science; Fading; Cellular network; Computation; Shadow mapping; Electronic engineering; Computer network; Context (archaeology); Channel (broadcasting); Topology (electrical circuits); Algorithm; Engineering; Electrical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003774209,0.001226494,0.001284834,0.00145827,0.000803351,0.001938179,0.002162439,0.001125448,0.001750238],"category_scores_gemma":[0.01372477,0.0006499354,0.0006521816,0.001761486,0.001828016,0.002816912,0.002203711,0.001391151,0.000335389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002227442,"about_ca_system_score_gemma":0.001347414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003357041,"about_ca_topic_score_gemma":0.001868574,"domain_scores_codex":[0.9975552,0.0008821659,0.00006926065,0.0003170753,0.000806968,0.0003693875],"domain_scores_gemma":[0.9911277,0.00561217,0.001195064,0.0004509157,0.001362554,0.0002514961],"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":[0.0000319022,0.00002630147,0.0006690095,0.00007263439,0.0000254742,0.0001065726,0.00006344318,0.9474035,0.0008595301,0.0432637,0.0004096025,0.007068292],"study_design_scores_gemma":[0.000001830624,0.00002018098,0.0001200458,0.000006218992,0.000005045163,0.00003958481,0.000015297,0.9950969,0.0001729878,0.004336448,0.0001800911,0.000005453312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05056189,0.001622657,0.9411587,0.000440197,0.00009238231,0.00005028303,0.00007435242,0.0001650322,0.005834609],"genre_scores_gemma":[0.9576434,0.001881967,0.03725061,0.0001546328,0.0001522111,0.0001027925,0.00009508154,0.00005159185,0.002667687],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003774209,"threshold_uncertainty_score":0.01996017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02008008345678788,"score_gpt":0.2561134467304341,"score_spread":0.2360333632736462,"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."}}