{"id":"W3026004538","doi":"10.1109/isit44484.2020.9174354","title":"Embedding Information in Radiation Pattern Fluctuations","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Interference (communication); Channel state information; Coding (social sciences); Interference alignment; Radiation pattern; Embedding; Channel (broadcasting); Context (archaeology); Radiation; SIGNAL (programming language); Electronic engineering; Antenna (radio); Telecommunications; Algorithm; Artificial intelligence; Wireless; Mathematics; MIMO; Statistics; Physics; Optics; Engineering; Geography","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":[0.0009352423,0.0007879054,0.0006444784,0.0004185387,0.0002580778,0.001110442,0.0005643301,0.0006977185,0.00162136],"category_scores_gemma":[0.006458289,0.0004023646,0.0003047917,0.0006319655,0.001147167,0.001610383,0.00132425,0.0008806436,0.0004389813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004091523,"about_ca_system_score_gemma":0.0005343354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005930623,"about_ca_topic_score_gemma":0.0004704606,"domain_scores_codex":[0.9992697,0.000308991,0.0000278802,0.0001174225,0.0001994519,0.00007664998],"domain_scores_gemma":[0.9975389,0.001362273,0.0003659003,0.0004511058,0.0002231626,0.00005856286],"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":[0.0002833512,0.00004688164,0.001300242,0.0001067205,0.00003218345,0.0001634936,0.00007197096,0.8500601,0.01827158,0.08445466,0.0009480473,0.04426085],"study_design_scores_gemma":[0.0000084005,0.00005100307,0.0004744563,0.00001331566,0.00000796725,0.00006605376,0.00001862091,0.9676579,0.004850664,0.02613247,0.0006974451,0.00002159952],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05772405,0.0002304062,0.9371177,0.000194564,0.00005069535,0.00001998577,0.0001032088,0.0002367833,0.00432252],"genre_scores_gemma":[0.9385306,0.0003935599,0.05765203,0.00009764534,0.0000520645,0.00005174557,0.0001163554,0.0001003463,0.003005657],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00162136,"threshold_uncertainty_score":0.005424023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01065049662440881,"score_gpt":0.2413976391617494,"score_spread":0.2307471425373405,"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."}}