{"id":"W2133447618","doi":"10.1109/iccad.1989.77016","title":"A diagnosis method using pseudo-random vectors without intermediate signatures","year":2003,"lang":"en","type":"article","venue":"","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Signature (topology); Pseudorandom number generator; Computer science; Fraction (chemistry); Combinational logic; Resolution (logic); Fault (geology); Algorithm; Scheme (mathematics); Computer engineering; Data mining; Theoretical computer science; Artificial intelligence; Logic gate; Mathematics","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":[0.0006318535,0.0007110301,0.0005649549,0.001765921,0.0004387257,0.001088713,0.001279434,0.001030798,0.004410961],"category_scores_gemma":[0.002616313,0.0003919719,0.0004403373,0.0005482657,0.0008280622,0.001600514,0.00100792,0.0009227049,0.001791109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006624881,"about_ca_system_score_gemma":0.0008220506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005914177,"about_ca_topic_score_gemma":0.0006791995,"domain_scores_codex":[0.9988932,0.0001891459,0.00007225128,0.0002518563,0.0005282999,0.00006520235],"domain_scores_gemma":[0.9987453,0.0004600256,0.0001132428,0.0002487806,0.0003771177,0.00005561542],"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":[0.0002968355,0.00008224041,0.0007078376,0.0002607629,0.00003890931,0.0002621531,0.0001336464,0.01891377,0.08348215,0.06662565,0.004773625,0.8244224],"study_design_scores_gemma":[0.0001681774,0.0004353201,0.0006646902,0.00007140025,0.00005872687,0.001931896,0.00004261577,0.7623779,0.1597899,0.03750981,0.03681748,0.000132167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001771279,0.00006774092,0.9960436,0.00005895168,0.00005200761,0.00004618323,0.00002276044,0.001151921,0.0007855953],"genre_scores_gemma":[0.1095722,0.0001505135,0.8847011,0.0001589068,0.00006141964,0.000145303,0.0001585041,0.0001473974,0.004904552],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004410961,"threshold_uncertainty_score":0.01475608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02936040818826101,"score_gpt":0.297521670914599,"score_spread":0.268161262726338,"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."}}