{"id":"W2051595364","doi":"10.1109/wcnc.2014.6952092","title":"The density penalty for random deployments in uplink CoMP networks","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Poisson point process; Telecommunications link; Coverage probability; Rayleigh fading; Computer science; Cellular network; Point process; Path loss; Mathematical optimization; Stochastic geometry; Grid; Outage probability; Position (finance); Algorithm; Computer network; Fading; Wireless; Mathematics; Telecommunications; Statistics; Channel (broadcasting)","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":[0.001267174,0.0005207793,0.0005647523,0.0004095891,0.0004702527,0.00080958,0.0009971529,0.000782364,0.001470476],"category_scores_gemma":[0.009484593,0.0004302414,0.0003337376,0.0004958343,0.001165045,0.001654004,0.001105531,0.0008754185,0.0003091694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001083356,"about_ca_system_score_gemma":0.0005902959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004223073,"about_ca_topic_score_gemma":0.002829072,"domain_scores_codex":[0.9992712,0.000275835,0.000022505,0.00008155019,0.0002024955,0.0001464035],"domain_scores_gemma":[0.9966865,0.002182452,0.0004193962,0.0002582051,0.0003333917,0.0001200392],"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":[0.00002880519,0.00001186295,0.0006558025,0.00002393684,0.000005591004,0.0001364643,0.00002721769,0.9598371,0.0005827936,0.03519791,0.0006713215,0.002821175],"study_design_scores_gemma":[0.00000213004,0.00001370581,0.0002112245,0.000005181383,0.000001881849,0.00005207492,0.00001257229,0.9932956,0.0001560698,0.005880929,0.0003639422,0.000004700341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08243563,0.0005704026,0.9060284,0.0009843785,0.00009359983,0.00004475551,0.0001255032,0.0002396816,0.009477607],"genre_scores_gemma":[0.9673795,0.0005135692,0.0281962,0.0002150203,0.00005649889,0.00009252461,0.00009695553,0.0001123919,0.003337379],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004223073,"threshold_uncertainty_score":0.008396983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006559613523120016,"score_gpt":0.2131968184420752,"score_spread":0.2066372049189552,"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."}}