{"id":"W2164564825","doi":"10.1109/ftcs.1991.146656","title":"Multiple fault analysis using a fault dropping technique","year":2002,"lang":"en","type":"article","venue":"","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Benchmark (surveying); Fault (geology); Set (abstract data type); Combinational logic; Stuck-at fault; Computer science; Automatic test pattern generation; Algorithm; Speedup; Electronic circuit; Fault coverage; Parallel computing; Fault detection and isolation; Logic gate; Engineering; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006649047,0.00106633,0.000972002,0.002689164,0.000664655,0.0009207249,0.001461001,0.0005167809,0.003417455],"category_scores_gemma":[0.001851625,0.0003987305,0.001403494,0.001572848,0.0006691081,0.001466359,0.001048898,0.001418602,0.0007670442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00083786,"about_ca_system_score_gemma":0.001359106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00259421,"about_ca_topic_score_gemma":0.002967787,"domain_scores_codex":[0.9991674,0.000099427,0.00004234244,0.0001221388,0.0004695961,0.00009907717],"domain_scores_gemma":[0.9986871,0.0004411362,0.00013666,0.0003036161,0.0003817686,0.00004973965],"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":[0.0003070894,0.0002014573,0.004268186,0.0002927354,0.000187236,0.0008953078,0.0002607531,0.2010922,0.1508205,0.0677486,0.004360091,0.5695658],"study_design_scores_gemma":[0.00002667472,0.0001206881,0.000698706,0.00002263353,0.00008203081,0.0004359897,0.00003156356,0.8947776,0.07062795,0.0259022,0.007241589,0.00003235419],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01084988,0.00007408879,0.98668,0.00003702485,0.00002310689,0.00004171575,0.00005308579,0.001473819,0.0007672817],"genre_scores_gemma":[0.2115155,0.0001752807,0.7834527,0.00009370897,0.00003907094,0.00008967212,0.0003736365,0.0005228661,0.003737483],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003417455,"threshold_uncertainty_score":0.01143253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04839260053106336,"score_gpt":0.2594121469517583,"score_spread":0.211019546420695,"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."}}