{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001530992,0.0008333967,0.0005761813,0.0004904977,0.0002889933,0.000810918,0.000673282,0.0006074585,0.001238581],"category_scores_gemma":[0.003951956,0.0002426887,0.0003257052,0.0005868868,0.0008109941,0.0006973711,0.0008279944,0.0004746508,0.0002525455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001086347,"about_ca_system_score_gemma":0.0006383702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001904814,"about_ca_topic_score_gemma":0.001343431,"domain_scores_codex":[0.9988444,0.0004163375,0.00002466258,0.0001222538,0.0004006392,0.0001917012],"domain_scores_gemma":[0.9967609,0.002090284,0.0003204125,0.0002079687,0.0005506051,0.00006980704],"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":[0.0002355503,0.00003774829,0.0009748578,0.00006319636,0.00003345538,0.000155592,0.00005235916,0.9676116,0.009961774,0.008481198,0.0003276585,0.01206497],"study_design_scores_gemma":[0.000009139217,0.0001141109,0.0004266016,0.000008911414,0.00001655833,0.00007267906,0.00003199472,0.9925548,0.004806705,0.00177183,0.00017592,0.00001070306],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2437426,0.000898908,0.7416615,0.0002741253,0.00004157507,0.00004686392,0.000121552,0.0004945925,0.01271827],"genre_scores_gemma":[0.9903977,0.0001248158,0.008790752,0.00002161931,0.00001030384,0.00001659403,0.00002658175,0.00001199167,0.0005997814],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001904814,"threshold_uncertainty_score":0.008096755,"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."}}