{"id":"W2164692194","doi":"10.1109/vetecf.1999.798643","title":"Enhanced capacity using adaptive transmission and receive diversity","year":2005,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Channel capacity; Computer science; Base station; Channel (broadcasting); Transmission (telecommunications); Enhanced Data Rates for GSM Evolution; Electronic engineering; Wireless; Topology (electrical circuits); Telecommunications; Computer network; Engineering; Electrical engineering","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":[0.0009336224,0.0003949438,0.0004812074,0.0005715057,0.0003016508,0.0008227297,0.000700984,0.0005615492,0.00231701],"category_scores_gemma":[0.004101154,0.0001986648,0.0003502938,0.0007643655,0.001208958,0.001300785,0.001305293,0.0006089546,0.0004195443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009679483,"about_ca_system_score_gemma":0.0004691802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001332042,"about_ca_topic_score_gemma":0.001133192,"domain_scores_codex":[0.9993283,0.0002210466,0.00001583771,0.00006299523,0.0002108594,0.0001610512],"domain_scores_gemma":[0.9967778,0.002245703,0.0001741054,0.0003868725,0.0003370268,0.00007848099],"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":[0.0003476337,0.00009044462,0.0006572081,0.00007275717,0.00004268966,0.0003006163,0.0001241059,0.8548692,0.02079891,0.07271563,0.002032016,0.04794873],"study_design_scores_gemma":[0.00003605829,0.00008891652,0.0003730663,0.00001390969,0.00002017776,0.0001666164,0.00002247992,0.9693013,0.007957233,0.02052495,0.001463847,0.00003133979],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2957798,0.001103984,0.667079,0.0005107766,0.0001138905,0.00004509577,0.000193304,0.001247611,0.03392649],"genre_scores_gemma":[0.9839756,0.0001772469,0.01404472,0.00005037339,0.0000424509,0.000030909,0.00004410097,0.00003353493,0.001601072],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00231701,"threshold_uncertainty_score":0.007751167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07882682836496377,"score_gpt":0.2879102833006423,"score_spread":0.2090834549356786,"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."}}