{"id":"W2979982950","doi":"10.3390/e21100992","title":"On Achievable Distortion in Sending Gaussian Sources over a Bandwidth-Matched Gaussian MAC with No Transmitter CSI","year":2019,"lang":"en","type":"article","venue":"Entropy","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Transmitter; Minimum mean square error; Fading; Channel state information; Gaussian; Rayleigh fading; Computer science; Mathematics; Algorithm; Upper and lower bounds; Decoding methods; Channel (broadcasting); Telecommunications; Topology (electrical circuits); Statistics; Wireless; Physics; Combinatorics; Mathematical analysis","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":[],"consensus_categories":[],"category_scores_codex":[0.00007292627,0.0002106972,0.0002415037,0.0001443095,0.00003527666,0.00002954607,0.00008476359,0.00008847981,0.0003314483],"category_scores_gemma":[0.000006240795,0.0001806057,0.0000413331,0.0001858816,0.0000139193,0.0002800931,0.000006695288,0.0001621775,0.0002431425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002252808,"about_ca_system_score_gemma":0.000007812821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003189136,"about_ca_topic_score_gemma":0.00003578302,"domain_scores_codex":[0.9989911,0.00003186626,0.0002333247,0.0002477419,0.0001707871,0.000325231],"domain_scores_gemma":[0.9995999,0.0000323024,0.00005118434,0.0002405266,0.00001168044,0.00006441571],"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":[0.0002628082,0.00007027375,0.04139405,0.0003363945,0.00005911464,0.00002581143,0.00198582,0.9357853,0.01783052,0.001398634,0.000371438,0.0004798119],"study_design_scores_gemma":[0.01989547,0.001397611,0.08681481,0.003581829,0.0001452527,0.00006080346,0.001162345,0.8170383,0.04352046,0.001011479,0.02155799,0.003813672],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.769887,0.0001071663,0.2221682,0.00008031381,0.0005311161,0.0006614382,0.00001086041,0.0003262712,0.006227648],"genre_scores_gemma":[0.9970459,0.00001599038,0.001831344,0.00004336988,0.00009394578,0.00003529213,0.000032372,0.00007205223,0.0008297079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2271589,"threshold_uncertainty_score":0.7364889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00292620355550865,"score_gpt":0.1878000057435607,"score_spread":0.1848738021880521,"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."}}