{"id":"W2579856090","doi":"10.1109/cefc.2016.7816128","title":"GPU optimization and implementation of Gaussian belief propagation algorithm","year":2016,"lang":"en","type":"article","venue":"","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Belief propagation; Graphics processing unit; Gaussian; CUDA; Parallel computing; Central processing unit; Sparse matrix; Gaussian elimination; Algorithm; Computational science; Computer hardware","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":[0.0001867639,0.0000547959,0.0000593435,0.00008357723,0.00003425216,0.00002368683,0.0001373773,0.00002441267,0.00002460927],"category_scores_gemma":[0.00001308339,0.00003704745,0.00001151371,0.0001443278,0.00001852952,0.0005009799,0.00007814063,0.00001683283,0.000001673046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002415536,"about_ca_system_score_gemma":0.00002449347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007249877,"about_ca_topic_score_gemma":0.0000227237,"domain_scores_codex":[0.9994386,0.00002824961,0.0001572512,0.0001681545,0.000122616,0.00008509482],"domain_scores_gemma":[0.9995914,0.00003104459,0.00009807709,0.000173821,0.00008137427,0.00002434814],"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":[5.608419e-7,0.00001144693,0.00129358,0.000005745838,0.000003151075,3.102794e-7,0.0003119838,0.00001197697,0.0071374,0.01229188,0.0001497946,0.9787822],"study_design_scores_gemma":[0.0007216817,0.0004602314,0.01120848,0.00008264693,0.000009179228,0.00002257009,0.0001560169,0.2306377,0.7504473,0.005771388,0.0001863291,0.0002964867],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003103082,0.000007627155,0.9950985,0.0008498727,0.00005826288,0.0001676624,9.01233e-7,0.0002329662,0.0004811402],"genre_scores_gemma":[0.4083194,0.00001452105,0.5915383,0.00002942362,0.0000099475,0.00001011938,8.999651e-7,0.000003384333,0.00007406217],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9784857,"threshold_uncertainty_score":0.1510751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009204596306334162,"score_gpt":0.2731455694190904,"score_spread":0.2639409731127562,"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."}}