{"id":"W2144406178","doi":"10.1109/tcomm.2009.04.070075","title":"Exact method for the error probability calculation of three-dimensional signal constellations","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Additive white Gaussian noise; Upper and lower bounds; Mathematics; Algorithm; Computation; Constellation diagram; White noise; Applied mathematics; Channel (broadcasting); Function (biology); Constellation; SIGNAL (programming language); Statistics; Mathematical analysis; Computer science; Telecommunications; Bit error rate; Physics; Decoding methods","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":[0.0003748134,0.0001729871,0.0002094737,0.0001355771,0.0005576737,0.00001730296,0.0007742166,0.0001067576,0.00004520388],"category_scores_gemma":[0.00001605466,0.0001544616,0.0001821604,0.0003977171,0.0002059174,0.0001668562,0.000004601892,0.0003703303,0.000004842857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001081163,"about_ca_system_score_gemma":0.00004987145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002757173,"about_ca_topic_score_gemma":0.0002218239,"domain_scores_codex":[0.9988809,0.0001224491,0.0005056961,0.0001531008,0.0001718491,0.0001659997],"domain_scores_gemma":[0.9952976,0.002156196,0.0001097132,0.002135987,0.0002512694,0.00004922339],"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":[0.00002325326,0.0002464794,0.000007636703,0.00001651989,0.00007256144,2.154071e-8,0.0001520663,0.8458839,0.008316468,0.005740579,0.0001849966,0.1393555],"study_design_scores_gemma":[0.0002692929,0.00007847365,0.000525959,0.00004192295,0.00008186822,0.000003010165,0.00002532515,0.9585124,0.02737916,0.01116012,0.001743553,0.0001788997],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0005412776,0.0003616078,0.9948875,0.001764768,0.00006470433,0.001121762,0.0001019258,0.0004578423,0.0006986295],"genre_scores_gemma":[0.7321841,0.0001029725,0.2673151,0.00005400173,0.000007451725,0.0002714286,0.00002047006,0.00001934572,0.00002509521],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7316428,"threshold_uncertainty_score":0.6298763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05733957994328678,"score_gpt":0.3285521754032389,"score_spread":0.2712125954599521,"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."}}