{"id":"W1970775648","doi":"10.1109/tvt.2014.2320830","title":"MAC-layer concurrent beamforming protocol for indoor millimeter-wave networks","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Beamforming; Codebook; Computer science; Physical layer; Throughput; Transmission (telecommunications); Interference (communication); Computer network; Electronic engineering; Wireless; Engineering; Telecommunications; Algorithm; 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":[0.0008990754,0.000728488,0.0005101472,0.0004057343,0.0006986767,0.0009120965,0.001154707,0.0004652239,0.00162309],"category_scores_gemma":[0.002590438,0.0002838495,0.0003287503,0.0008476389,0.0005434583,0.00144747,0.001401992,0.0009992764,0.0003636993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006383449,"about_ca_system_score_gemma":0.001234525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001547038,"about_ca_topic_score_gemma":0.001927299,"domain_scores_codex":[0.9992353,0.0001855613,0.00004713988,0.000107236,0.0003221297,0.0001027154],"domain_scores_gemma":[0.9984327,0.0007178657,0.000180154,0.0001744405,0.0004318167,0.0000629653],"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":[0.00030518,0.0002128092,0.001259497,0.0006178522,0.000169918,0.0006393938,0.0004363827,0.4287629,0.0840909,0.1728821,0.007018507,0.3036047],"study_design_scores_gemma":[0.0000232585,0.0001344702,0.0001721911,0.00002003355,0.00004108771,0.0002147502,0.00005797015,0.9693595,0.01059703,0.0136822,0.00567068,0.00002673695],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005308459,0.0005379706,0.9912566,0.0001352266,0.00006781529,0.00006574838,0.00002481667,0.0001681169,0.002435228],"genre_scores_gemma":[0.7481857,0.001313247,0.2445923,0.0003198736,0.0001546117,0.0005527025,0.0001429494,0.00005906636,0.004679535],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00162309,"threshold_uncertainty_score":0.005429804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0317521893615052,"score_gpt":0.2623299798007305,"score_spread":0.2305777904392253,"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."}}