{"id":"W2097596696","doi":"10.1109/ds-rt.2007.19","title":"Efficient Load Balancing Schemes for Large-Scale Real-Time HLA/RTI Based Distributed Simulations","year":2007,"lang":"en","type":"article","venue":"","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Distributed computing; Scheduling (production processes); Prioritization; Load balancing (electrical power); Quality of service; High-level architecture; Architecture; Response time; Real-time computing; Computer network; Operating system; Interoperability","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002848764,0.0001492564,0.0002295939,0.0001893289,0.0004368017,0.0001494031,0.0003901082,0.0001094758,0.001438429],"category_scores_gemma":[0.001413076,0.0001173965,0.000170903,0.001143425,0.00004021385,0.00007598809,0.00006607164,0.00007173837,0.0002182754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001236159,"about_ca_system_score_gemma":0.0001116071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002365393,"about_ca_topic_score_gemma":0.00005163917,"domain_scores_codex":[0.9973702,0.00003168905,0.000786045,0.0004976252,0.0009080653,0.0004063754],"domain_scores_gemma":[0.9947569,0.003226538,0.0002109983,0.0007063919,0.000932535,0.0001665882],"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":[0.0004026085,0.002555938,0.04910108,0.00002984727,0.00006101392,0.000004426688,0.0007984514,0.5742155,0.1116686,0.09747444,0.1232656,0.04042255],"study_design_scores_gemma":[0.0005490701,0.00002570647,0.006005628,0.000006464721,0.00001002158,3.476295e-7,0.0001365948,0.868738,0.01227805,0.003113908,0.108973,0.0001631919],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1527899,0.000006397726,0.8409277,0.000666626,0.00004481684,0.0006199967,0.0003417578,0.0003149091,0.004287877],"genre_scores_gemma":[0.9350837,2.973979e-7,0.06237534,0.000255399,0.00006769109,0.00003521076,0.0001351838,0.00001475717,0.002032362],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7822939,"threshold_uncertainty_score":0.9994744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04652633293123748,"score_gpt":0.3921165006845607,"score_spread":0.3455901677533232,"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."}}