{"id":"W4403165803","doi":"10.61091/jcmcc122-11","title":"Efficient Task Scheduling for Large-scale Graph Data Processing in Cloud Computing: A Particle Swarm Optimization Approach","year":2024,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Cloud computing; Distributed computing; Scheduling (production processes); Particle swarm optimization; Theoretical computer science; Mathematical optimization; Algorithm; Mathematics; Operating system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.005312123,0.000351844,0.000727083,0.0003671985,0.000432866,0.001155669,0.001512475,0.0001512224,4.499554e-7],"category_scores_gemma":[0.000306268,0.0003130659,0.0001750408,0.001129616,0.00005549509,0.0001297807,0.0013268,0.0005594647,6.6518e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001180307,"about_ca_system_score_gemma":0.0002015178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004750445,"about_ca_topic_score_gemma":2.363956e-7,"domain_scores_codex":[0.9963529,0.0001468605,0.001425374,0.0006602192,0.0007688001,0.0006458113],"domain_scores_gemma":[0.997589,0.0005780614,0.0006914573,0.0005953711,0.0003453787,0.0002007571],"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":[0.00003993052,0.001138371,0.00003786104,0.0009852352,0.00007082234,0.00002798901,0.005988565,0.6629277,0.00004973266,0.3230297,0.0000980614,0.005605991],"study_design_scores_gemma":[0.002767285,0.0002647002,0.000007918357,0.0009931567,0.00007623425,0.00006988847,0.0007377038,0.9617591,0.00004079181,0.03270123,0.0002493017,0.000332711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2275907,0.001260616,0.7630451,0.000217416,0.00722901,0.0004079538,0.00000225169,0.0001241111,0.0001229474],"genre_scores_gemma":[0.7918117,0.000007416026,0.2068295,0.00002295146,0.001283926,0.000002395489,0.000003280143,0.00003550522,0.000003305161],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.564221,"threshold_uncertainty_score":0.9999322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02210148694589723,"score_gpt":0.2698786528056236,"score_spread":0.2477771658597263,"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."}}