{"id":"W2108530390","doi":"10.1109/iccad.1990.129926","title":"On the diagnostic resolution of signature analysis","year":2002,"lang":"en","type":"article","venue":"","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Signature (topology); Benchmark (surveying); Computer science; Algorithm; Very-large-scale integration; Resolution (logic); Simple (philosophy); Simplicity; Theoretical computer science; Data mining; Mathematics; Artificial intelligence; Embedded system; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001413138,0.00004300778,0.00006989557,0.0000791749,0.00006762117,0.00002531403,0.0003574684,0.00002276569,0.0001453328],"category_scores_gemma":[0.0005176772,0.00002497436,0.00006842627,0.0009651385,0.00001725589,0.0000645689,0.00003437517,0.0000717839,0.00003547519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006852588,"about_ca_system_score_gemma":0.000002685335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002013746,"about_ca_topic_score_gemma":0.000009242884,"domain_scores_codex":[0.9995018,0.00004032959,0.00009082023,0.0001233702,0.0001490528,0.00009465003],"domain_scores_gemma":[0.9984604,0.001145787,0.00004213072,0.0003001381,0.00003224493,0.00001937297],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[8.787061e-8,0.0001573921,0.006613872,0.000006934039,0.0001808412,0.00001480491,0.0007640471,0.01376095,0.0007921794,0.8681023,0.01574085,0.09386575],"study_design_scores_gemma":[0.00005788341,0.00005573947,0.01433136,0.00001531011,0.00005249538,0.000001424531,0.00001638612,0.9785706,0.0006798788,0.005987138,0.0001432517,0.00008846648],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03761289,0.0003242824,0.907038,0.003279424,0.00006777239,0.00007725184,0.000001008268,0.0001188909,0.05148048],"genre_scores_gemma":[0.9989415,0.000006156713,0.0003022404,0.0004278598,0.00001375389,0.000001616147,2.906804e-7,0.000001188282,0.0003053583],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9648097,"threshold_uncertainty_score":0.1591292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02259010165920621,"score_gpt":0.2074275069820617,"score_spread":0.1848374053228555,"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."}}