{"id":"W2043502750","doi":"10.1145/2597652.2597679","title":"Supporting storage configuration for I/O intensive workflows","year":2014,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Department of Energy","keywords":"Workflow; Provisioning; Computer science; Distributed computing; Workflow management system; Resource allocation; Database; Workflow engine; Workflow technology; Operating system; Computer network","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001584199,0.0008467658,0.0006953212,0.0005095219,0.001013465,0.001649907,0.001187429,0.0006163245,0.001210558],"category_scores_gemma":[0.006305861,0.000464189,0.00035819,0.0006667585,0.0007699901,0.001810078,0.0009813551,0.0009964117,0.0003526688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009055436,"about_ca_system_score_gemma":0.00239187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005622483,"about_ca_topic_score_gemma":0.004975969,"domain_scores_codex":[0.9992942,0.0002153294,0.0000444295,0.0001434954,0.0001623336,0.0001401837],"domain_scores_gemma":[0.9961272,0.001986889,0.0005862637,0.0007212797,0.0003577642,0.0002206786],"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":[0.001095242,0.000417837,0.02948516,0.000285557,0.00004986685,0.0004078704,0.0005251937,0.7573263,0.05910493,0.003934723,0.002413943,0.1449535],"study_design_scores_gemma":[0.00002001338,0.0001045335,0.003029281,0.00001615117,0.00001619179,0.0000768546,0.0001102343,0.9644493,0.02826149,0.003062613,0.0008236836,0.00002963264],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5950257,0.0005056861,0.3847689,0.0004457071,0.0000596069,0.0001953559,0.0002650596,0.01515376,0.003580214],"genre_scores_gemma":[0.9629852,0.0001107787,0.03620878,0.00002422566,0.00001195335,0.00003294866,0.0001285762,0.0001198429,0.0003777404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005622483,"threshold_uncertainty_score":0.01117951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01479753714464688,"score_gpt":0.2617495380153128,"score_spread":0.2469520008706659,"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."}}