{"id":"W2102406450","doi":"10.1109/glocom.2004.1378154","title":"A new approach to calculating the exact transition probability and bit error probability of arbitrary two-dimensional signaling","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Additive white Gaussian noise; Fading; Computer science; Probability of error; Algorithm; Channel (broadcasting); Bit error rate; Computation; Theoretical computer science; Bit (key); Constellation; Mathematics; Telecommunications; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001478311,0.0008685911,0.0008106719,0.001973739,0.0004091483,0.001046041,0.001827043,0.0009688529,0.003090265],"category_scores_gemma":[0.006826373,0.0004731479,0.0007583538,0.00118148,0.001262799,0.00224397,0.001241819,0.001444812,0.0008638576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008798829,"about_ca_system_score_gemma":0.0009778244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001251569,"about_ca_topic_score_gemma":0.001276382,"domain_scores_codex":[0.9988837,0.0002580608,0.00006604572,0.0001234867,0.0006019875,0.00006683087],"domain_scores_gemma":[0.9973908,0.001466215,0.0001797791,0.0004423347,0.0004616803,0.00005917397],"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":[0.00008081306,0.00007803346,0.0008516371,0.0001929206,0.0000745825,0.0002584065,0.0001539493,0.6334815,0.009169011,0.2476938,0.001152971,0.1068124],"study_design_scores_gemma":[0.000007178564,0.00002869219,0.000162003,0.00001874521,0.0000109499,0.0001603845,0.00001104778,0.958718,0.002807813,0.03631406,0.00173165,0.00002954133],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001278279,0.00007097513,0.9978268,0.00001201607,0.00001913269,0.00001281393,0.00001775565,0.0001029214,0.0006592872],"genre_scores_gemma":[0.1385115,0.0006700385,0.8575684,0.00007508029,0.00007969256,0.0002291949,0.0001151899,0.0001601003,0.002590804],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003090265,"threshold_uncertainty_score":0.01033795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03012983035824594,"score_gpt":0.2639562681419724,"score_spread":0.2338264377837265,"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."}}