{"id":"W4403864210","doi":"10.23919/annsim61499.2024.10732112","title":"Brooks-Iyengar Algorithm in pub/sub Architecture Using the DEVS Formalism","year":2024,"lang":"en","type":"article","venue":"","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"DEVS; Formalism (music); Architecture; Computer science; Algorithm; Theoretical computer science; Parallel computing; Modeling and simulation; History; Simulation; Art; Archaeology","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":[0.001222734,0.00008775009,0.0001001864,0.0002357106,0.0001407975,0.0004329462,0.000460181,0.00005996131,0.0003430339],"category_scores_gemma":[0.0001280133,0.00004565439,0.00008017819,0.001121154,0.00005533717,0.0001814639,0.0001092642,0.0002067743,0.0001541932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003214353,"about_ca_system_score_gemma":0.00005360851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009278422,"about_ca_topic_score_gemma":0.00006857704,"domain_scores_codex":[0.9986317,0.00006006696,0.0003654578,0.0002730582,0.0004996696,0.0001700022],"domain_scores_gemma":[0.9987136,0.0007214206,0.00003558523,0.0004183735,0.00006928747,0.00004175454],"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":[0.000001608649,0.00001449601,0.0001629482,0.000002255387,0.000004873452,0.000004696271,0.0008076933,0.002890141,0.0008699659,0.04686173,0.00683752,0.9415421],"study_design_scores_gemma":[0.00006224747,0.000008856919,0.0006500303,0.00001518487,0.000004354018,0.00002323674,0.0003764715,0.5049948,0.003799379,0.2062261,0.283725,0.000114513],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04808222,0.0002455404,0.9334719,0.003335549,0.0001539704,0.000347907,0.00001257665,0.0002158818,0.01413442],"genre_scores_gemma":[0.9557756,0.000008664828,0.0409074,0.0007944409,0.0001368553,0.00003596433,0.000002831618,0.00001275653,0.002325475],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9414275,"threshold_uncertainty_score":0.417491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1306307388001709,"score_gpt":0.4394042443474191,"score_spread":0.3087735055472483,"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."}}