{"id":"W2606302229","doi":"10.1145/3030207.3030229","title":"Conducting Repeatable Experiments in Highly Variable Cloud Computing Environments","year":2017,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cloud computing; Benchmark (surveying); Computer science; Variable (mathematics); Control (management); Distributed computing; Computer engineering; Operating system; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007859922,0.000180888,0.0002194219,0.0000878127,0.000783834,0.0006022758,0.001902407,0.00005491238,0.00001679294],"category_scores_gemma":[0.00006370145,0.0001692065,0.00004384651,0.0001028983,0.00005429133,0.000128973,0.002408076,0.0001717539,0.00008313824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009902572,"about_ca_system_score_gemma":0.00001793375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006593721,"about_ca_topic_score_gemma":0.00000331641,"domain_scores_codex":[0.9981216,0.00006959598,0.000344273,0.0006390008,0.0003099104,0.0005156038],"domain_scores_gemma":[0.9979891,0.00005852903,0.0002381735,0.001613582,0.00001001004,0.00009065427],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004247639,0.002287322,0.09500556,0.0001844324,0.000376448,0.0007433131,0.01201416,0.1379494,0.04061075,0.5200636,0.01072281,0.1799998],"study_design_scores_gemma":[0.003398295,0.000149807,0.01637509,0.0003256044,0.00001394746,0.00003480787,0.0007428228,0.9031162,0.02164932,0.003906523,0.04905481,0.001232726],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7156397,0.00009519429,0.1582875,0.00066398,0.001637095,0.0002670284,3.37004e-7,0.0002233833,0.1231858],"genre_scores_gemma":[0.9415192,0.000001716637,0.05168924,0.0002478192,0.0001597471,0.000004181264,6.99708e-7,0.00001184963,0.006365535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7651668,"threshold_uncertainty_score":0.6900041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04958635084348046,"score_gpt":0.2730522795999201,"score_spread":0.2234659287564397,"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."}}