{"id":"W2963021833","doi":"10.1109/tit.2017.2673805","title":"On the VLSI Energy Complexity of LDPC Decoder Circuits","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Information Theory","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Very-large-scale integration; Low-density parity-check code; Decoding methods; Computer science; Electronic circuit; Energy (signal processing); Forward error correction; Electronic engineering; Algorithm; Mathematics; Electrical engineering; Engineering; Embedded system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000720432,0.0001327814,0.0001292133,0.0001809834,0.0007860661,0.0001958371,0.001342168,0.00007301693,0.00007453138],"category_scores_gemma":[0.00006234652,0.0001012715,0.0001080126,0.0001186817,0.0002347085,0.001539625,0.000007791226,0.0002166873,0.00007717657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005174909,"about_ca_system_score_gemma":0.00005119665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006070003,"about_ca_topic_score_gemma":0.00002877104,"domain_scores_codex":[0.9989647,0.0001272785,0.0003225067,0.0001213583,0.0003019142,0.0001622513],"domain_scores_gemma":[0.9977099,0.0004126497,0.0003552558,0.001327977,0.0001509713,0.00004320774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001687083,0.00005207115,0.000001626568,0.000009208537,0.00001993124,2.489965e-7,0.001369064,0.001019487,0.0001298986,0.8376865,0.0004059515,0.1592892],"study_design_scores_gemma":[0.000524123,0.0003295127,0.000578895,0.0001532071,0.00002143425,0.00002289044,0.0002473113,0.06366418,0.3608215,0.571353,0.001851055,0.0004328872],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003363409,0.000002318927,0.9698349,0.0006256643,0.0006639932,0.000129868,0.0000111473,0.0002751922,0.02509354],"genre_scores_gemma":[0.9970241,0.000007405058,0.001824087,0.0009295561,0.00001043258,0.0000418666,8.411213e-7,0.000006139058,0.0001555259],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9936607,"threshold_uncertainty_score":0.6045864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03635577643927789,"score_gpt":0.2647097784756325,"score_spread":0.2283540020363546,"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."}}