{"id":"W2956974697","doi":"10.1109/icc.2019.8762072","title":"PhyCode: A Practical Wireless Communication System Exploiting Superimposed Signals","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Full-Duplex Wireless Communications","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Wireless; SIGNAL (programming language); Exploit; Offset (computer science); Software-defined radio; Decoding methods; Distortion (music); Carrier frequency offset; Compensation (psychology); Electronic engineering; Frequency offset; Real-time computing; Telecommunications; Channel (broadcasting); Orthogonal frequency-division multiplexing; Bandwidth (computing); Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006162736,0.0005734536,0.0008018828,0.0002193504,0.0001870258,0.0003312987,0.001576975,0.0006739054,0.000152273],"category_scores_gemma":[0.00009792529,0.0006323871,0.0002452487,0.0002236094,0.00009112745,0.0003217098,0.001710195,0.002063648,0.0005895304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006304648,"about_ca_system_score_gemma":0.0001927645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001832525,"about_ca_topic_score_gemma":0.00004754371,"domain_scores_codex":[0.9972074,0.000398525,0.0009720243,0.0004834746,0.0004372324,0.0005013419],"domain_scores_gemma":[0.9941047,0.001027928,0.0002254619,0.004230301,0.0002522175,0.0001593676],"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":[0.0000126294,0.0001095868,0.0001205932,0.002448925,0.000341126,0.000007151437,0.001283976,0.959516,0.01741874,0.01511211,0.00263591,0.0009932854],"study_design_scores_gemma":[0.0003132037,0.00001216676,0.0001145445,0.001173752,0.00008060486,0.00003021287,0.002180282,0.9897407,0.004627462,0.00002103401,0.001001015,0.0007050498],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8973782,0.002114209,0.05181799,0.0009147215,0.0009044629,0.002125438,0.0001174559,0.005508123,0.03911938],"genre_scores_gemma":[0.9766279,0.0006458571,0.02109484,0.00004412474,0.0001069264,0.0005762585,0.0004763876,0.0002231372,0.0002045388],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07924971,"threshold_uncertainty_score":0.9996127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04399801981238154,"score_gpt":0.2830853499531488,"score_spread":0.2390873301407673,"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."}}