{"id":"W2101838504","doi":"10.1145/764808.764814","title":"Iterative decoding in analog CMOS","year":2003,"lang":"en","type":"article","venue":"","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"CMOS; Computer science; Low-density parity-check code; Decoding methods; Turbo code; Electronic engineering; Electronic circuit; Coding (social sciences); Analogue electronics; Hamming distance; Algorithm; Electrical engineering; Engineering; Mathematics","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":[0.0002229453,0.0002844206,0.0001809159,0.0002718611,0.0002494924,0.0007172617,0.0005420927,0.0005222731,0.002389127],"category_scores_gemma":[0.0009696138,0.000134562,0.0002098019,0.0003056868,0.0002866414,0.0007191827,0.0003404254,0.0003616499,0.0008721577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004869289,"about_ca_system_score_gemma":0.0004728862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009844769,"about_ca_topic_score_gemma":0.001355947,"domain_scores_codex":[0.999688,0.00004641564,0.00001975764,0.00004251567,0.00017682,0.00002642929],"domain_scores_gemma":[0.9997432,0.00008382308,0.00002185392,0.00003587564,0.0001063608,0.000008962368],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002441851,0.00007368124,0.00102968,0.0004439294,0.00006163623,0.0005293763,0.000360889,0.1191641,0.2317221,0.2470498,0.003191003,0.3961295],"study_design_scores_gemma":[0.0000796973,0.0004545936,0.0005955755,0.000141576,0.00007370613,0.001304265,0.00007919166,0.6740257,0.2049938,0.0563899,0.06179606,0.00006604084],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0211277,0.001112355,0.9494,0.0002391215,0.0001707771,0.00006968343,0.00006989222,0.000978587,0.02683186],"genre_scores_gemma":[0.5276066,0.001427244,0.4569125,0.0003664385,0.000107773,0.00009957545,0.0001092973,0.00006442411,0.01330615],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002389127,"threshold_uncertainty_score":0.007992446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01920809034637836,"score_gpt":0.2750883874898317,"score_spread":0.2558802971434533,"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."}}