{"id":"W2218379410","doi":"10.1109/iccd.2015.7357083","title":"Emulation-based selection and assessment of assertion checkers for post-silicon validation","year":2015,"lang":"en","type":"article","venue":"","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"University of Illinois at Urbana-Champaign","keywords":"Assertion; Emulation; Computer science; Hardware emulation; Selection (genetic algorithm); Crash; Software bug; Embedded system; Reliability engineering; Computer engineering; Software; Programming language; Artificial intelligence; Engineering; Field-programmable gate array","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":[0.00717537,0.00160675,0.0006633505,0.001402837,0.0003202375,0.0008128014,0.001659385,0.0008586784,0.002721648],"category_scores_gemma":[0.03331232,0.0004944981,0.000406049,0.0003683288,0.0006146696,0.001248935,0.0008656865,0.0008219699,0.0006608155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005763345,"about_ca_system_score_gemma":0.001101589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000416458,"about_ca_topic_score_gemma":0.0008430407,"domain_scores_codex":[0.993046,0.003837549,0.0006637143,0.0006823958,0.001326808,0.0004435176],"domain_scores_gemma":[0.9530956,0.02769858,0.004808961,0.006890946,0.006826902,0.0006789412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002492395,0.001633067,0.02453955,0.001178262,0.0002526928,0.0005579971,0.0004330536,0.1224981,0.580638,0.003915652,0.001976493,0.2598847],"study_design_scores_gemma":[0.0002658392,0.002249643,0.005078257,0.0000972585,0.0001832901,0.0003847968,0.00009369024,0.4353702,0.5515209,0.00157513,0.003111851,0.00006913348],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3488868,0.0005094414,0.6367797,0.0001849426,0.0001039431,0.0008519175,0.0003574845,0.01052897,0.00179689],"genre_scores_gemma":[0.800111,0.0001107588,0.1976876,0.0001193718,0.0000261418,0.0005000175,0.0003653564,0.0004779307,0.0006017637],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00717537,"threshold_uncertainty_score":0.03794742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05666402753882063,"score_gpt":0.3257038350045994,"score_spread":0.2690398074657787,"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."}}