{"id":"W1490086049","doi":"10.1109/iscas.1993.394019","title":"An efficient global search algorithm for test generation","year":2002,"lang":"en","type":"article","venue":"1993 IEEE International Symposium on Circuits and Systems","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Combinational logic; Benchmark (surveying); Automatic test pattern generation; Algorithm; Computer science; Electronic circuit; Test (biology); Logic gate; 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":[0.0009552112,0.001562334,0.001228344,0.001840334,0.0008004218,0.00125018,0.001598361,0.001400239,0.01216108],"category_scores_gemma":[0.003277201,0.0006231415,0.001006377,0.001681005,0.0009417685,0.001819746,0.001594403,0.001557375,0.003586866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000809793,"about_ca_system_score_gemma":0.001443955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002147199,"about_ca_topic_score_gemma":0.002297429,"domain_scores_codex":[0.9989123,0.0003043544,0.00006182956,0.0002437941,0.0003556002,0.0001221604],"domain_scores_gemma":[0.9988968,0.0005589889,0.00005447584,0.0001884161,0.0002697047,0.00003165259],"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":[0.0002224621,0.0001181896,0.0005007986,0.0002388233,0.00006302523,0.0001715008,0.00009605013,0.2435126,0.009057708,0.03948789,0.01872195,0.687809],"study_design_scores_gemma":[0.0001429295,0.0001237891,0.0001617254,0.00003231459,0.00003594976,0.0002483366,0.00002674154,0.93525,0.004815422,0.04579163,0.01334536,0.00002582104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001438334,0.0001278309,0.9945597,0.00007033522,0.00002365203,0.00006955417,0.00007564882,0.001845012,0.001789925],"genre_scores_gemma":[0.0553246,0.0001651303,0.9395375,0.000145003,0.00003749688,0.0003825747,0.0007188845,0.0004763778,0.003212387],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01216108,"threshold_uncertainty_score":0.04068285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05765914944621985,"score_gpt":0.2892554301974697,"score_spread":0.2315962807512498,"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."}}