{"id":"W1885763295","doi":"10.1002/wcm.2337","title":"SNR and throughput analysis of distributed collaborative beamforming in locally‐scattered environments","year":2012,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"EMS (Canada); Institut National de la Recherche Scientifique","funders":"","keywords":"Computer science; Beamforming; Overhead (engineering); Throughput; Quantization (signal processing); Algorithm; Ideal (ethics); Computer engineering; Mathematical optimization; Mathematics; Telecommunications; Wireless","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":[0.000236118,0.0001063557,0.0002470989,0.000162126,0.0001102197,0.00001804824,0.0001365347,0.00004722914,0.000003804411],"category_scores_gemma":[0.00000593244,0.0001129085,0.00002793878,0.0004614556,0.00008531753,0.0001245359,0.0002110022,0.0001168832,5.042402e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003819208,"about_ca_system_score_gemma":0.000005433996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002460235,"about_ca_topic_score_gemma":0.00002944315,"domain_scores_codex":[0.9992726,0.00005680056,0.0003329739,0.000101586,0.00006609361,0.0001699635],"domain_scores_gemma":[0.9993637,0.0001095707,0.00007539515,0.0003718817,0.00002225715,0.00005725919],"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":[0.00001576941,0.0004979212,0.1528671,0.0002479735,0.0013642,6.495407e-7,0.03697828,0.4168991,0.08229204,0.001039776,0.00002111933,0.3077761],"study_design_scores_gemma":[0.0002420902,0.00001303016,0.008726661,0.00005347723,0.000100062,9.611676e-7,0.001589399,0.986459,0.002149206,0.0000091208,0.0005211206,0.0001358518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7082623,0.002756117,0.2886693,0.00001393637,0.00001630135,0.000140846,0.00002568519,0.00002116493,0.00009430087],"genre_scores_gemma":[0.9916326,0.001529844,0.006664915,0.00001394434,0.00000691689,0.00002254291,0.0001160426,0.00001125348,0.00000196673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.56956,"threshold_uncertainty_score":0.4604276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01657851973659023,"score_gpt":0.2534740691872243,"score_spread":0.236895549450634,"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."}}