{"id":"W4407301939","doi":"10.1016/j.procs.2025.01.040","title":"EM-ACO-ARM: An Enhanced Multiple Ant Colony Optimization Algorithm for Adaptive Resource Management in Cloud Environment","year":2025,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Computer science; Ant colony optimization algorithms; Cloud computing; ANT; Resource (disambiguation); Distributed computing; Algorithm; Operating system; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001283212,0.0003059509,0.0002869706,0.0006165273,0.0005086003,0.0004560048,0.002518771,0.00006731447,0.000001800664],"category_scores_gemma":[0.00002328274,0.000301699,0.00007421002,0.001670237,0.000215544,0.0002187677,0.001852847,0.0001648534,0.000008004582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003574427,"about_ca_system_score_gemma":0.0001158046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001266882,"about_ca_topic_score_gemma":0.000004366415,"domain_scores_codex":[0.9965034,0.0000788673,0.0004806277,0.001521458,0.0006345382,0.000781162],"domain_scores_gemma":[0.9985225,0.0001482745,0.0001746303,0.0008744091,0.0001075896,0.0001725745],"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":[0.00001461092,0.0002989225,0.00002456421,0.00002861055,0.00001438163,0.000007428325,0.001247427,0.530807,0.0000316502,0.003278838,0.000192721,0.4640538],"study_design_scores_gemma":[0.001090438,0.0003538499,0.0006531306,0.00009197144,0.00001052201,0.000002594783,0.0001831353,0.9935483,0.0007631328,0.0008091297,0.002155086,0.0003387575],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009181228,0.00007123048,0.9871459,0.0003788079,0.0008507028,0.001381084,0.000002275128,0.0002515327,0.0007372567],"genre_scores_gemma":[0.2050411,0.00001136075,0.7935684,0.0007305455,0.0001595214,0.0002147106,0.000003902237,0.00001282216,0.0002576164],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4637151,"threshold_uncertainty_score":0.9999435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01010522958732076,"score_gpt":0.2323401826704773,"score_spread":0.2222349530831566,"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."}}