{"id":"W2129848580","doi":"10.1109/ccece.2008.4564771","title":"An Ant Colony Optimization approach for test pattern generation","year":2008,"lang":"en","type":"article","venue":"Conference proceedings - Canadian Conference on Electrical and Computer Engineering","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ant colony optimization algorithms; Benchmark (surveying); Automatic test pattern generation; Computer science; Fault coverage; Test set; Set (abstract data type); Electronic circuit; Algorithm; Combinational logic; Logic gate; Artificial intelligence; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001414833,0.0002871641,0.0002675136,0.0003247606,0.0003713688,0.0005297093,0.000554872,0.0001373246,0.000004480435],"category_scores_gemma":[0.00006680135,0.0002944701,0.00004122857,0.0004151266,0.00003491699,0.0005900207,0.00003523136,0.000244521,0.000001535124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001164422,"about_ca_system_score_gemma":0.0003813112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006460571,"about_ca_topic_score_gemma":0.0001022745,"domain_scores_codex":[0.9982052,0.000008116802,0.000262132,0.0006978631,0.0001943085,0.0006323502],"domain_scores_gemma":[0.9987383,0.0000571656,0.00007615252,0.0001587405,0.0003959721,0.0005736575],"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":[0.000002156551,0.0004045639,0.01345649,0.0001984449,0.000068628,0.00006038848,0.002964317,0.09395672,0.009561086,0.1029448,0.001266531,0.7751159],"study_design_scores_gemma":[0.0002527906,0.0005172378,0.001263248,0.00002917387,0.000006085403,0.00009552329,0.000006266147,0.9970688,0.0002567305,0.00004217391,0.0000718954,0.0003900274],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01450452,0.00002629924,0.9842108,0.0002712745,0.00009350896,0.0003148771,0.000006795634,0.0002207054,0.0003511695],"genre_scores_gemma":[0.9622378,0.00003358111,0.03680921,0.0004490666,0.0003202731,0.00007870009,0.00003064378,0.00001981993,0.00002085414],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9477333,"threshold_uncertainty_score":0.9999508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03227123950221634,"score_gpt":0.2016947658982965,"score_spread":0.1694235263960802,"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."}}