{"id":"W4241595802","doi":"10.36227/techrxiv.12107043","title":"Hybrid Precoding for Millimeter Wave RoF Systems","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Advanced Photonic Communication Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Precoding; Zero-forcing precoding; Path loss; Electronic engineering; Extremely high frequency; Computer science; Radio frequency; Beamforming; Transmission (telecommunications); Photonics; Telecommunications; Wireless; Engineering; Physics; MIMO; 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":[0.0001458793,0.0002700934,0.0002121247,0.0001435077,0.0001695868,0.0004944531,0.0002782696,0.000433886,0.001789423],"category_scores_gemma":[0.0003611133,0.0001143826,0.0001921696,0.0002245283,0.0002938877,0.0005956469,0.0003285467,0.0003214727,0.0003760294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003311555,"about_ca_system_score_gemma":0.0002645761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001758358,"about_ca_topic_score_gemma":0.001853551,"domain_scores_codex":[0.9998562,0.00003871655,0.000003880806,0.00002231431,0.00006072791,0.00001806986],"domain_scores_gemma":[0.9998485,0.00005740682,0.00002136253,0.00002442215,0.00004214939,0.000006155949],"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":[0.00008951512,0.00003280958,0.0005050792,0.00008972135,0.00005371181,0.0001507355,0.00009878832,0.769688,0.02546398,0.08786745,0.002127106,0.1138331],"study_design_scores_gemma":[0.000006388661,0.0000379206,0.000109926,0.000004698768,0.000004406594,0.00005467663,0.00001078522,0.9896526,0.001948804,0.006175582,0.001987404,0.000006813841],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03018471,0.00056355,0.95937,0.0001809455,0.00005610334,0.0000203519,0.00005692388,0.0001929957,0.009374482],"genre_scores_gemma":[0.8894835,0.0007083133,0.09817203,0.000155752,0.00006764541,0.00006195693,0.00007886143,0.0000317566,0.01124018],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001789423,"threshold_uncertainty_score":0.005986214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07689131015847475,"score_gpt":0.2725292790260559,"score_spread":0.1956379688675812,"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."}}