{"id":"W2135442224","doi":"10.1109/distra.2005.18","title":"DEVStone: a benchmarking technique for studying performance of DEVS modeling and simulation environments","year":2005,"lang":"en","type":"article","venue":"","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"DEVS; Computer science; Benchmarking; Modular design; Benchmark (surveying); Modeling and simulation; Metric (unit); Discrete event simulation; Process (computing); Variety (cybernetics); Distributed computing; Simulation; Programming language; Artificial intelligence; 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":[0.001072822,0.00007730539,0.0001324428,0.0001474321,0.000158733,0.00003514431,0.0001631934,0.00005187897,0.00005922757],"category_scores_gemma":[0.00009595582,0.00006297264,0.00003735666,0.0001912972,0.00002624161,0.0003021329,0.00006785893,0.00004047397,0.000003509794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002502594,"about_ca_system_score_gemma":0.00001061884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004067128,"about_ca_topic_score_gemma":0.000002841813,"domain_scores_codex":[0.9987919,0.00001600526,0.0004966761,0.0002431061,0.0003440718,0.0001082125],"domain_scores_gemma":[0.9990802,0.0004241376,0.0001444177,0.0002382958,0.00007828981,0.00003467695],"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":[0.00001407239,0.00003037811,0.006180514,0.000003889636,0.000003156935,9.93008e-9,0.0001548535,0.8404388,0.006091528,0.0006793602,0.00001685441,0.1463866],"study_design_scores_gemma":[0.0001488005,0.00004217524,0.001195215,0.000009072714,0.000004917385,4.863205e-7,0.00007749486,0.9824535,0.01244128,0.001740026,0.001811891,0.00007508574],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4266309,0.00001458306,0.5725822,0.00003363263,0.000004819307,0.0004217077,0.000001593367,0.00001599795,0.0002945545],"genre_scores_gemma":[0.8558367,0.0000107751,0.1438118,0.00004583008,0.00002792962,0.0001107709,0.00000211569,0.000006078983,0.0001479344],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4292058,"threshold_uncertainty_score":0.256795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.130776045029114,"score_gpt":0.4079224607262839,"score_spread":0.2771464156971699,"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."}}