{"id":"W4287831525","doi":"10.1145/3543849","title":"The DEVStone Metric: Performance Analysis of DEVS Simulation Engines","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Ministerio de Ciencia e Innovación","keywords":"DEVS; Benchmark (surveying); Discrete event simulation; Metric (unit); Computer science; Formalism (music); Performance metric; Modeling and simulation; Simulation; 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":[0.001152176,0.0001162822,0.0002136754,0.0008648887,0.00125985,0.0001089833,0.0004407023,0.00003986821,0.00005123612],"category_scores_gemma":[0.00007994505,0.00008954685,0.0001539001,0.003087024,0.00003281605,0.0001981524,0.00003411084,0.0001596967,0.000002556834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000415392,"about_ca_system_score_gemma":0.00002184922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002423434,"about_ca_topic_score_gemma":0.000005958994,"domain_scores_codex":[0.9979667,0.0001296407,0.0006436739,0.0003329879,0.0007965383,0.0001304743],"domain_scores_gemma":[0.9959559,0.002755777,0.0001979293,0.0006977732,0.0003495109,0.00004304168],"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":[0.00002346045,0.00003079173,0.000209177,7.90683e-7,0.00005216618,2.972486e-8,0.000167008,0.7392313,0.000003386685,0.0001575069,0.000001877419,0.2601225],"study_design_scores_gemma":[0.0001594264,0.00008174157,0.001615348,0.000002049987,0.0001339844,3.634891e-7,0.00009288856,0.9941806,0.00002849006,0.002743531,0.0008635219,0.00009810421],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2988578,0.00004779202,0.700657,0.0001401512,0.00007381885,0.0001419481,0.00001270501,0.00005132884,0.000017477],"genre_scores_gemma":[0.9925612,0.00002739381,0.007170401,0.00007421655,0.0000223847,0.00004041065,0.00001365438,0.000008743461,0.00008163417],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6937034,"threshold_uncertainty_score":0.9689876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1012050368631543,"score_gpt":0.3780876981216702,"score_spread":0.2768826612585159,"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."}}