{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003339346,0.0001864941,0.000184901,0.000126391,0.0001436089,0.00005378643,0.0001922225,0.0001705441,0.00003461256],"category_scores_gemma":[0.00002270761,0.0002361451,0.00008504749,0.00006028203,0.00003572753,0.0001638939,0.0002703397,0.0003362308,0.00001339525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001222291,"about_ca_system_score_gemma":0.00001913724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006039938,"about_ca_topic_score_gemma":0.000001243381,"domain_scores_codex":[0.9992789,0.00008345268,0.0001476805,0.0002994436,0.00003552978,0.0001550114],"domain_scores_gemma":[0.9993209,0.0001431008,0.00008135974,0.0003394868,0.00005885858,0.00005628628],"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":[0.00003081577,0.00000952147,0.0001225605,0.0001318047,0.00006038202,8.802475e-7,0.0006408995,0.9923898,0.002135655,0.004128143,0.00002358195,0.0003259509],"study_design_scores_gemma":[0.0004782534,0.00002744063,0.00001326487,0.0001096314,0.00006389576,0.000001704725,0.001017746,0.9611893,0.03045229,0.005921938,0.0004061019,0.000318447],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4481958,0.0003648279,0.5496454,0.00000368408,0.0001223985,0.0002660672,0.000004732088,0.0001311367,0.001265969],"genre_scores_gemma":[0.9971761,0.0003472003,0.001501657,0.00001587251,0.00003587174,0.000004174039,0.0001380814,0.00003827193,0.0007428285],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5489802,"threshold_uncertainty_score":0.9629719,"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."}}