{"id":"W2114726247","doi":"10.1109/isit.2004.1365331","title":"Density evolution analysis of device mismatch in analog decoders","year":2004,"lang":"en","type":"article","venue":"","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Analogue electronics; Analog multiplier; Decoding methods; Electronic engineering; Electronic circuit; Power (physics); Algorithm; Electrical engineering; Computer hardware; Analog signal; Engineering; Physics","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":[0.0004781425,0.0002624244,0.0003913204,0.000492806,0.0003252004,0.0004923039,0.0005173203,0.0006215842,0.001370949],"category_scores_gemma":[0.004532524,0.0002946258,0.0001588219,0.0003855687,0.0005352282,0.001008393,0.0004256092,0.0003715614,0.0002220856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001288784,"about_ca_system_score_gemma":0.0003209925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001999636,"about_ca_topic_score_gemma":0.001309877,"domain_scores_codex":[0.9997204,0.00006430121,0.000009286528,0.00003160867,0.0001418641,0.0000325776],"domain_scores_gemma":[0.9987313,0.0008460002,0.0001279075,0.0000673959,0.0001914004,0.00003602314],"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":[0.0002306534,0.00006158138,0.005459905,0.0001143913,0.0000434352,0.0003760459,0.0002956796,0.7347072,0.03818709,0.2039611,0.0008957788,0.01566715],"study_design_scores_gemma":[0.000003173884,0.00001340728,0.0004646207,0.000003667039,0.00000358751,0.00005292577,0.00001079029,0.9896952,0.003360521,0.006111166,0.0002737811,0.00000718853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6677949,0.0011002,0.313668,0.0007345277,0.00004199816,0.00005801917,0.0001339069,0.0004074357,0.01606101],"genre_scores_gemma":[0.9901407,0.0001177218,0.007811959,0.0000385319,0.0000106625,0.00001897416,0.00003847338,0.00002933042,0.001793648],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001999636,"threshold_uncertainty_score":0.009350836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01434814421794318,"score_gpt":0.270680590669402,"score_spread":0.2563324464514589,"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."}}