{"id":"W2126750376","doi":"10.1109/jssc.2006.881554","title":"Weak Cell Detection in Deep-Submicron SRAMs: A Programmable Detection Technique","year":2006,"lang":"en","type":"article","venue":"IEEE Journal of Solid-State Circuits","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"CMC Microsystems","keywords":"Static random-access memory; Chip; Electronic engineering; Voltage; Limiting; Computer science; Embedded system; Computer hardware; Engineering; Electrical engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001189214,0.0002602974,0.0003820282,0.0006647811,0.0001743392,0.000228794,0.0006671252,0.0001505112,0.000002366952],"category_scores_gemma":[0.0000482614,0.0002589969,0.0001813105,0.001089292,0.00004977646,0.001139801,0.00004089631,0.0006617975,0.000017412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003657861,"about_ca_system_score_gemma":0.0001516499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001914103,"about_ca_topic_score_gemma":0.0004666711,"domain_scores_codex":[0.9974134,0.0001580826,0.0009886521,0.0003525449,0.0004549422,0.0006324001],"domain_scores_gemma":[0.9983197,0.00008785514,0.0008094254,0.000294007,0.0003459652,0.0001430342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000001274277,0.000161535,0.0005310978,0.00004371789,0.000008867122,0.0001456948,0.0001954512,0.003567713,0.6157408,0.000008879447,0.00001841815,0.3795766],"study_design_scores_gemma":[0.001057922,0.0004930297,0.003506494,0.0002157608,0.00002240819,0.001565136,0.00007129747,0.01551031,0.9716529,0.004769014,0.000697509,0.0004381749],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2598101,0.0002547535,0.7383049,0.00003021923,0.0005325611,0.0002695477,0.00000114916,0.0001080906,0.0006887834],"genre_scores_gemma":[0.9986199,0.00004030907,0.0008413245,0.00003833594,0.0003119652,0.00002307985,4.710302e-7,0.00002900812,0.00009559422],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7388098,"threshold_uncertainty_score":0.9999862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01055151925284666,"score_gpt":0.2292406880373054,"score_spread":0.2186891687844587,"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."}}