{"id":"W3015389560","doi":"10.1109/pimrc48278.2020.9217248","title":"Hybrid Preceding for Millimeter Wave RoF Systems","year":2020,"lang":"en","type":"article","venue":"","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Precoding; Computer science; Path loss; Zero-forcing precoding; Electronic engineering; Extremely high frequency; Radio frequency; Beamforming; Photonics; Transmission (telecommunications); Radio over fiber; Interference (communication); Telecommunications; Wireless; Engineering; MIMO; Physics; Channel (broadcasting); Optics","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":[0.0001268473,0.0002923295,0.0002057204,0.0001777909,0.0001944676,0.0005525563,0.0004022244,0.0005207391,0.00219651],"category_scores_gemma":[0.0002601329,0.0001138049,0.0002141614,0.0002045742,0.0002906035,0.0007639552,0.0003978797,0.000382772,0.0005625584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002795396,"about_ca_system_score_gemma":0.0002172287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001264386,"about_ca_topic_score_gemma":0.001546575,"domain_scores_codex":[0.999878,0.00002801926,0.000003167729,0.00002061659,0.0000542772,0.00001583531],"domain_scores_gemma":[0.9998832,0.00003573137,0.00001916356,0.00002297913,0.00003299095,0.00000593839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008248253,0.00004461356,0.000771252,0.000138005,0.00006700373,0.0002476494,0.0001269441,0.6815543,0.03517029,0.1603808,0.002673301,0.1187435],"study_design_scores_gemma":[0.00000616438,0.00005953748,0.0002017603,0.000008761667,0.000007266892,0.0001212906,0.00002205954,0.9798788,0.002353252,0.0114244,0.005905184,0.00001152302],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02172747,0.0007900788,0.9627951,0.0001478526,0.00006506009,0.00002536761,0.00005763466,0.0002219647,0.01416955],"genre_scores_gemma":[0.8820436,0.001211145,0.1017781,0.0001725097,0.00007968135,0.00009805826,0.00009499764,0.00004323924,0.01447869],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00219651,"threshold_uncertainty_score":0.00734812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06170463850765043,"score_gpt":0.220580187955441,"score_spread":0.1588755494477906,"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."}}