{"id":"W1849362294","doi":"10.1109/icecs.2001.957544","title":"New embedded memory architecture for enhanced yield, performance and power consumption","year":2002,"lang":"en","type":"article","venue":"","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Redundancy (engineering); Computer science; Power consumption; Architecture; Memory architecture; Embedded system; Computer architecture; Parallel computing; Yield (engineering); Power (physics); Operating system; Materials science","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":[0.0001026103,0.00009075682,0.0001086778,0.00004840286,0.00009776378,0.00009926753,0.0001705085,0.00005720796,0.0003214659],"category_scores_gemma":[0.0000123476,0.00007186241,0.00003789325,0.00006558798,0.00001306602,0.0002058222,0.00003927651,0.00007051683,0.00004815038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001017812,"about_ca_system_score_gemma":0.000006231392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000731337,"about_ca_topic_score_gemma":0.00001991602,"domain_scores_codex":[0.9993455,0.00001449901,0.0001464367,0.0002347055,0.00008654677,0.0001722836],"domain_scores_gemma":[0.9995481,0.00008304512,0.00004352149,0.0002162878,0.00003720861,0.00007177436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006254803,0.00006961438,0.0002932981,0.0001643495,0.00007767287,0.000003089337,0.01233896,0.002131924,0.01573602,0.03174367,0.2332937,0.7040852],"study_design_scores_gemma":[0.002269834,0.0009372939,0.001266201,0.0002199778,0.00001376885,0.0002214656,0.0001936536,0.9025103,0.04076451,0.001442003,0.04927848,0.000882474],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06755416,0.0001305008,0.9187708,0.0003969577,0.0006808161,0.000212289,3.478596e-7,0.000107554,0.01214651],"genre_scores_gemma":[0.9676021,0.00002519182,0.0170936,0.0004715263,0.0001224329,0.00001583465,3.162011e-7,0.000005051866,0.01466399],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9016773,"threshold_uncertainty_score":0.3519826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02284104387793833,"score_gpt":0.2259284683849344,"score_spread":0.203087424506996,"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."}}