{"id":"W4399036954","doi":"10.29007/rdbb","title":"Efficient Simulation for Hardware Model Checking","year":2024,"lang":"en","type":"article","venue":"EPiC series in computing","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Correctness; Executable; Model checking; Semantics (computer science); Programming language; Formal verification; Set (abstract data type); Speedup; Symbolic trajectory evaluation; Computer engineering; Parallel computing; Theoretical computer science","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":[0.0006220936,0.0001183306,0.0001305455,0.0001571372,0.0001346365,0.0002428854,0.0003576558,0.0000522328,8.886457e-7],"category_scores_gemma":[0.0004662916,0.0001190588,0.00005740986,0.0003855488,0.00002242156,0.0001307036,0.0002245284,0.0001266535,0.000002831428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008541405,"about_ca_system_score_gemma":0.00005961048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008032932,"about_ca_topic_score_gemma":8.648358e-7,"domain_scores_codex":[0.9989353,0.00002410356,0.0002537379,0.0003844512,0.0001414533,0.0002608941],"domain_scores_gemma":[0.9987133,0.0008832903,0.00004182013,0.0002803722,0.00005298731,0.00002829249],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002612727,0.000008012116,0.0001793364,0.00006581711,0.000002752281,0.000006170028,0.001403386,0.9181532,0.00001250513,0.01133344,0.0002731509,0.06855967],"study_design_scores_gemma":[0.00009481988,0.00002573935,0.00009207541,0.000302536,0.000001904829,0.000007871607,0.000006648887,0.9559586,0.0001539671,0.04293624,0.0002857064,0.0001338639],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01661246,0.0002620738,0.9742263,0.0002930118,0.0005556115,0.0002022331,9.618702e-7,0.007550149,0.0002972265],"genre_scores_gemma":[0.6183277,4.299349e-7,0.3814787,0.00006501054,0.00007270491,0.000009358452,0.000001211285,0.000009817826,0.00003512056],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6017152,"threshold_uncertainty_score":0.4855079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0436413897169171,"score_gpt":0.3310387987670756,"score_spread":0.2873974090501585,"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."}}