{"id":"W2098271807","doi":"10.1109/hpcs.2007.6","title":"An Adaptive Double-layer Workflow Scheduling Approach for Grid Computing","year":2007,"lang":"en","type":"article","venue":"","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Distributed computing; Grid; Grid computing; Granularity; Scheduling (production processes); Workflow; Workflow management system; Database; Mathematical optimization; Operating system","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":[0.001853967,0.0002308962,0.0002713052,0.0001200481,0.0003382547,0.0003445259,0.001209373,0.0001182774,0.000002513235],"category_scores_gemma":[0.00001148311,0.0002060243,0.0001217327,0.0005213948,0.00003856033,0.0004162486,0.0001655424,0.0001762037,0.00001699969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005294364,"about_ca_system_score_gemma":0.00005947315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004781079,"about_ca_topic_score_gemma":0.00000553193,"domain_scores_codex":[0.9978419,0.00004761961,0.0004356608,0.0006765226,0.0002970186,0.0007012713],"domain_scores_gemma":[0.9986187,0.0002008609,0.0001518596,0.0006041809,0.0001983896,0.0002260682],"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":[0.0002786511,0.0005909295,0.001770908,0.00009195875,0.0001313559,0.00002052581,0.002708384,0.5359545,0.0005351526,0.3779779,0.002071837,0.07786789],"study_design_scores_gemma":[0.0009352227,0.0001775304,0.0002611029,0.00002805984,0.00000542072,0.00002325162,0.0002426053,0.9956328,0.0006026793,0.0004189117,0.001345739,0.0003266197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009086956,0.00007001397,0.9765775,0.0000400745,0.0008954087,0.0004647278,0.000003066783,0.0006271255,0.01223516],"genre_scores_gemma":[0.5391164,1.401404e-7,0.4601629,0.0001075526,0.0005067795,0.000003921611,0.00002420322,0.000009623549,0.00006841905],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5300295,"threshold_uncertainty_score":0.8401428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05560480459334161,"score_gpt":0.3015066614690031,"score_spread":0.2459018568756615,"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."}}