{"id":"W4211129328","doi":"10.36227/techrxiv.12107043.v1","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; Radio over fiber; Telecommunications; Wireless; Engineering; MIMO; Physics; 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":[0.0001451738,0.0002664586,0.0002000898,0.0001475581,0.0001660209,0.0004697004,0.0002761679,0.0004240959,0.001622298],"category_scores_gemma":[0.0003714417,0.0001052541,0.0001742116,0.0002182958,0.0002877764,0.0006055523,0.0003159257,0.0003146617,0.0003866628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002725841,"about_ca_system_score_gemma":0.0002259549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001219738,"about_ca_topic_score_gemma":0.001299266,"domain_scores_codex":[0.9998505,0.00003811249,0.000004031376,0.00002167142,0.00006917549,0.00001653633],"domain_scores_gemma":[0.9998435,0.00005681299,0.0000217014,0.00002858227,0.00004330335,0.000006189637],"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":[0.00009659013,0.00003792363,0.0005835483,0.0001119333,0.00005916792,0.0001780995,0.0001097815,0.6817687,0.03865087,0.1297721,0.002283075,0.1463483],"study_design_scores_gemma":[0.000007563759,0.00005085965,0.0001457028,0.000006264856,0.000005388019,0.00008629039,0.00001419784,0.982133,0.003353242,0.01090999,0.003278903,0.000008626418],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02481925,0.0005235925,0.9665189,0.0001489655,0.00004798117,0.00001657277,0.00004647058,0.0001637102,0.00771458],"genre_scores_gemma":[0.8540366,0.000868983,0.1338024,0.0001601682,0.00007869562,0.00006407146,0.00008471205,0.00003674482,0.01086761],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001622298,"threshold_uncertainty_score":0.005427122,"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."}}