{"id":"W4289655226","doi":"10.1109/isit50566.2022.9834835","title":"Converting a 1×K Static Rayleigh Channel to K Parallel AWGN Using Media-based Modulation","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Symposium on Information Theory (ISIT)","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Ciena (Canada)","funders":"","keywords":"Additive white Gaussian noise; Independent and identically distributed random variables; Channel (broadcasting); Topology (electrical circuits); Algorithm; Modulation (music); Computer science; Decoding methods; Telecommunications; Mathematics; Random variable; Physics; Statistics; Combinatorics; Acoustics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005610485,0.0002393226,0.0001980922,0.0005984259,0.0003510374,0.00008531909,0.0008275348,0.0000691042,0.0004182066],"category_scores_gemma":[0.0001523087,0.0002801286,0.0000853495,0.0004642492,0.00004277467,0.0009588847,0.0001853785,0.0004083788,0.0001395546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009685347,"about_ca_system_score_gemma":0.00003548703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000985345,"about_ca_topic_score_gemma":0.000001908797,"domain_scores_codex":[0.9980214,0.0001159727,0.0006927499,0.0001726161,0.0007268363,0.0002704844],"domain_scores_gemma":[0.9986843,0.0003619283,0.0002516978,0.000476108,0.0001506029,0.00007530436],"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":[0.0001157307,0.00002819172,0.00002999734,0.00001966399,0.00004333575,0.000001231722,0.001475523,0.9765713,0.003949195,0.01381169,0.0004134265,0.003540739],"study_design_scores_gemma":[0.0006717575,0.0000593492,0.0001119825,0.00003365981,0.000007628093,0.000007135,0.001500555,0.9778211,0.009935075,0.005688814,0.003835593,0.0003274203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1918274,0.00002974871,0.7993433,0.001284455,0.002208046,0.0006630988,0.0002559324,0.001246803,0.003141268],"genre_scores_gemma":[0.9949059,0.00001998267,0.002918186,0.001230852,0.00005829977,0.0004003949,0.0003799432,0.00003920771,0.00004722977],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8030785,"threshold_uncertainty_score":0.9999651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01690535446655446,"score_gpt":0.2484736210892677,"score_spread":0.2315682666227133,"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."}}