{"id":"W2116036098","doi":"10.1142/s0218126611008031","title":"ERROR RECOVERY IN CONTINUOUS VALUED NUMBER SYSTEM","year":2011,"lang":"en","type":"article","venue":"Journal of Circuits Systems and Computers","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Windsor","funders":"","keywords":"Redundancy (engineering); Computer science; Implementation; Error detection and correction; Computer hardware; Electronic circuit; Set (abstract data type); Arithmetic; Algorithm; Mathematics; Engineering; Electrical 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005439186,0.0001726231,0.0005012614,0.0002101403,0.00002807917,0.00006662236,0.0001908787,0.0001075076,0.000006050654],"category_scores_gemma":[0.000004625671,0.0001495833,0.00007149258,0.000158539,0.00001924885,0.0003752011,0.00001492439,0.0002367144,0.00002192198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001440831,"about_ca_system_score_gemma":0.00002801435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000433283,"about_ca_topic_score_gemma":0.000001879987,"domain_scores_codex":[0.9986323,0.00007023443,0.0007141081,0.0001087917,0.000222851,0.0002517845],"domain_scores_gemma":[0.9994022,0.00004081648,0.000213861,0.0001434959,0.00007624816,0.0001233867],"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":[0.0006072121,0.001125541,0.2994228,0.02117002,0.005774393,0.01134259,0.07011048,0.3127341,0.01502933,0.0290147,0.08514059,0.1485283],"study_design_scores_gemma":[0.02099561,0.003063326,0.2352706,0.02304213,0.0006018127,0.03666484,0.01586417,0.6392777,0.002506615,0.0003235566,0.01753412,0.004855502],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9581155,0.001225675,0.02839875,0.000003415124,0.005757272,0.0002054829,0.000002798913,0.00008680848,0.006204294],"genre_scores_gemma":[0.9993056,0.00004071132,0.0003183894,0.00001205625,0.0002496648,0.000003614555,3.228524e-7,0.00003041052,0.00003921493],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3265436,"threshold_uncertainty_score":0.6099831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01703311312161451,"score_gpt":0.1918477283446743,"score_spread":0.1748146152230598,"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."}}