{"id":"W2152287700","doi":"10.5555/1162708.1162819","title":"Channel based sequential simulation","year":2005,"lang":"en","type":"article","venue":"Winter Simulation Conference","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Discrete event simulation; Computer science; Asynchronous communication; Timestamp; Queue; Event (particle physics); Implementation; Channel (broadcasting); Real-time computing; Algorithm; Distributed computing; Parallel computing; Simulation; Computer network","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":[0.0008183098,0.0004878527,0.0007880684,0.0004979954,0.0006390995,0.001061623,0.001023782,0.0006554886,0.009740224],"category_scores_gemma":[0.002570543,0.0002600728,0.0005110194,0.0006407043,0.00065632,0.001310626,0.001327868,0.000705988,0.0011526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008280981,"about_ca_system_score_gemma":0.001966507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004572093,"about_ca_topic_score_gemma":0.003684338,"domain_scores_codex":[0.9991814,0.0001944988,0.00003755451,0.0001371658,0.0003467802,0.0001025834],"domain_scores_gemma":[0.9983721,0.0008119946,0.00008648861,0.0002739263,0.0003425902,0.0001127927],"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":[0.0002907208,0.0000781972,0.001102124,0.00009853324,0.00003235605,0.0001257142,0.0000776008,0.8312183,0.004887265,0.1004848,0.003686498,0.05791785],"study_design_scores_gemma":[0.00002683049,0.00002867734,0.00006015906,0.000003420414,0.000008264723,0.00002466784,0.000006711641,0.9804617,0.001264225,0.01488603,0.003222777,0.000006482893],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009903411,0.0001160836,0.9748889,0.0001034316,0.0001099529,0.000111789,0.0001416946,0.001337028,0.01328778],"genre_scores_gemma":[0.676895,0.0004427552,0.3017761,0.0001690517,0.0001113009,0.0004715055,0.0004642493,0.0003294767,0.01934068],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009740224,"threshold_uncertainty_score":0.03258431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2515144314822211,"score_gpt":0.4575409034868052,"score_spread":0.206026472004584,"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."}}