{"id":"W3010791201","doi":"10.1109/tvt.2020.2982178","title":"Performance Analysis and Enhancement of Beamforming Training in 802.11ad","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Beamforming; Electronic engineering; Computer science; Training (meteorology); Engineering; Physics","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":[0.001551832,0.0009739376,0.0004513057,0.0006009864,0.0003784704,0.0007180095,0.0005660202,0.0004909154,0.0008366195],"category_scores_gemma":[0.004221018,0.000280877,0.0003020473,0.0007002969,0.0006355443,0.001105251,0.0006245982,0.0005424669,0.0002523154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009497961,"about_ca_system_score_gemma":0.0008191262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00274772,"about_ca_topic_score_gemma":0.002461479,"domain_scores_codex":[0.9985771,0.0004118398,0.00004976112,0.0001263326,0.0006050369,0.000229843],"domain_scores_gemma":[0.997673,0.001288144,0.0002324001,0.0002161286,0.0005541752,0.00003615089],"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":[0.0003408857,0.0001427337,0.00585086,0.0002326761,0.00006178534,0.00026148,0.0001917791,0.7922192,0.05284324,0.02672966,0.000875859,0.1202497],"study_design_scores_gemma":[0.00000555843,0.0001446134,0.000961597,0.00001197523,0.0000210171,0.0001312676,0.00002774306,0.9881066,0.008752027,0.00124169,0.0005821763,0.00001370769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1921791,0.002609988,0.7909454,0.0003546986,0.00006055129,0.00007084431,0.00007361895,0.0006396193,0.01306607],"genre_scores_gemma":[0.9683546,0.001046559,0.02921347,0.00005542737,0.00002843584,0.0000348443,0.00004611219,0.0000264205,0.001194137],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00274772,"threshold_uncertainty_score":0.008207023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01763104474217612,"score_gpt":0.2104750006860693,"score_spread":0.1928439559438932,"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."}}