{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004306416,0.0001725654,0.000170785,0.00007551665,0.0002657064,0.0006890126,0.0005870737,0.00007686928,0.000005852381],"category_scores_gemma":[0.00002820677,0.000159183,0.00006102769,0.0001634672,0.00002890999,0.0002738986,0.00002680314,0.00008417666,0.00003508777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001575207,"about_ca_system_score_gemma":0.00001895912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001136206,"about_ca_topic_score_gemma":0.000005604631,"domain_scores_codex":[0.9981962,0.00005946668,0.0003339033,0.0005615578,0.0005510276,0.0002978574],"domain_scores_gemma":[0.9990359,0.000158431,0.0001028984,0.0002821043,0.0002596335,0.0001610233],"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":[5.4843e-7,0.001001518,0.004796814,0.00005817068,0.0001010445,0.00004890102,0.001100942,0.05625974,0.03928867,0.05101394,0.002569052,0.8437607],"study_design_scores_gemma":[0.0003952278,0.0002489106,0.0003933023,0.00004351543,0.000004675098,0.0001043363,0.00002276038,0.9970615,0.000408676,0.00002483554,0.001098282,0.0001940117],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05569144,0.0001934717,0.9341419,0.0007025507,0.003836248,0.0004841356,0.0001596945,0.0001897234,0.004600835],"genre_scores_gemma":[0.9977335,0.00001675347,0.0003198757,0.000200529,0.001332251,0.00005310643,0.00002263526,0.00001134823,0.0003100298],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9420421,"threshold_uncertainty_score":0.6644164,"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."}}