{"id":"W3216086173","doi":"10.36227/techrxiv.18586103.v1","title":"Performance of Reconfigurable Intelligent Surfaces in the Presence of Generalized Gaussian Noise","year":2022,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Rayleigh fading; Gaussian noise; Fading; Gaussian; Noise (video); Mathematics; Additive white Gaussian noise; Modulation (music); Algorithm; Applied mathematics; Expression (computer science); Diversity gain; Topology (electrical circuits); Telecommunications; Computer science; Channel (broadcasting); Physics; Combinatorics; Acoustics; Artificial intelligence","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":[0.0007034122,0.0007130604,0.0006386796,0.0003127485,0.000320495,0.0008658977,0.0004606522,0.0007894374,0.0003807667],"category_scores_gemma":[0.00280518,0.0001338604,0.0002843371,0.0003448174,0.00131626,0.0008129934,0.0008248955,0.000358627,0.0001384732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004309367,"about_ca_system_score_gemma":0.00032033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009514363,"about_ca_topic_score_gemma":0.0004890129,"domain_scores_codex":[0.9991535,0.0002778694,0.0000252909,0.0001235456,0.0002151566,0.0002046918],"domain_scores_gemma":[0.9979854,0.001191789,0.0003294782,0.0001920745,0.0002333729,0.00006793703],"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":[0.000665618,0.00004372749,0.00329844,0.00008488152,0.0000706634,0.0006349985,0.0001827926,0.8953179,0.08168597,0.006330404,0.0001169937,0.01156774],"study_design_scores_gemma":[0.00001167146,0.0002869034,0.0009270926,0.00000906216,0.00002368236,0.000178702,0.0000859989,0.9673674,0.02961765,0.001328165,0.0001394225,0.00002409697],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9378682,0.0002685885,0.05847405,0.00008185708,0.0000175211,0.000006786634,0.00001574997,0.000125257,0.00314195],"genre_scores_gemma":[0.9984215,0.0000409806,0.001326228,0.000009101603,0.00000243101,0.00000229046,0.000005064713,0.000003115754,0.000189395],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009514363,"threshold_uncertainty_score":0.003720045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02171794036774809,"score_gpt":0.2403025929364938,"score_spread":0.2185846525687457,"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."}}