{"id":"W2996787524","doi":"10.48550/arxiv.1912.12406","title":"Beamforming Learning for mmWave Communication: Theory and Experimental Validation","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Beamforming; Computer science; Electronic engineering; Telecommunications; 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":[0.005603632,0.001141315,0.0008067971,0.001119969,0.000835478,0.001318372,0.001548054,0.001991682,0.006043759],"category_scores_gemma":[0.02304925,0.0004619118,0.0005933736,0.001214716,0.001494602,0.00214275,0.001756581,0.002076783,0.001955076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001059019,"about_ca_system_score_gemma":0.001255361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002869974,"about_ca_topic_score_gemma":0.001834644,"domain_scores_codex":[0.9959765,0.001350925,0.0001885401,0.0004747198,0.001670028,0.0003392802],"domain_scores_gemma":[0.9837287,0.01070947,0.0008859664,0.001620693,0.002738497,0.0003166403],"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":[0.00145631,0.001832171,0.00645912,0.001582012,0.0002121147,0.0002101411,0.0003490192,0.5614991,0.0476348,0.03359148,0.009101422,0.3360724],"study_design_scores_gemma":[0.0001318217,0.001272433,0.002057937,0.0001877857,0.00004494761,0.0001665144,0.0001709355,0.9352516,0.04019188,0.01580913,0.00464814,0.00006701723],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07803135,0.003345782,0.8962159,0.001238694,0.0004606999,0.0005933227,0.000651453,0.001496149,0.01796666],"genre_scores_gemma":[0.6964067,0.00294157,0.2926849,0.0008223215,0.0001474581,0.0009379099,0.001396476,0.0002056124,0.004457144],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006043759,"threshold_uncertainty_score":0.02963519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06476054518338767,"score_gpt":0.1984934508946333,"score_spread":0.1337329057112456,"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."}}