{"id":"W2097091845","doi":"10.1109/ccnc08.2007.52","title":"Impact of Finite Precision Arithmetics on EXIT Chart Analysis of Turbo Codes","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Turbo code; Computer science; Turbo; EXIT chart; Serial concatenated convolutional codes; Coding (social sciences); Arithmetic coding; Chart; Algorithm; Double-precision floating-point format; Decoding methods; Arithmetic; Theoretical computer science; Concatenated error correction code; Mathematics; Computation; Data compression; Context-adaptive binary arithmetic coding; Block code; Statistics; Engineering","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":[0.003628208,0.0009201803,0.0008295113,0.00129599,0.0005961788,0.001790078,0.0006006337,0.0007303503,0.002335822],"category_scores_gemma":[0.03644792,0.0002908408,0.0003961294,0.0008956374,0.002064001,0.002476528,0.0011185,0.001349392,0.0002612805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008845802,"about_ca_system_score_gemma":0.0009350735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00187034,"about_ca_topic_score_gemma":0.0008746456,"domain_scores_codex":[0.9975616,0.00111202,0.00008148072,0.0001242942,0.0009073783,0.0002133005],"domain_scores_gemma":[0.9751305,0.02028367,0.001361712,0.001222321,0.001791682,0.0002101388],"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":[0.000445066,0.00004005609,0.001825966,0.000138448,0.00003191891,0.0003559383,0.0002015852,0.8540869,0.008906309,0.1002033,0.0006509271,0.03311362],"study_design_scores_gemma":[0.000007163264,0.00008704756,0.0002899542,0.00003225755,0.000007660803,0.00006352983,0.00003188904,0.9781387,0.008875394,0.01213489,0.0003074788,0.00002408041],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1992465,0.001270057,0.787385,0.0004157269,0.00009397816,0.00005137065,0.00009807818,0.0009120537,0.01052725],"genre_scores_gemma":[0.9676682,0.0006711229,0.03004534,0.00004952017,0.00005106065,0.00003272759,0.00006807388,0.0001399436,0.001273936],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003628208,"threshold_uncertainty_score":0.01918805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02891676661960709,"score_gpt":0.303003587271149,"score_spread":0.2740868206515419,"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."}}