{"id":"W2015213058","doi":"10.1109/infocom.2014.6847950","title":"Venice: Reliable virtual data center embedding in clouds","year":2014,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":124,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Cloud computing; Data center; Provisioning; Quality of service; Distributed computing; Scheduling (production processes); High availability; Embedding; Reliability (semiconductor); Virtual machine; Computer network; Service (business); Server; Database; Operating system; Engineering","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":[0.0008059145,0.00009634205,0.0001177836,0.00007972158,0.00007230879,0.0001429194,0.002070038,0.00003311049,0.00001513841],"category_scores_gemma":[0.00004177854,0.00008167334,0.00002298193,0.000272532,0.00001558486,0.00005437556,0.002588905,0.0001245489,0.0001464554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002672639,"about_ca_system_score_gemma":0.00001105231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008133982,"about_ca_topic_score_gemma":0.00002406707,"domain_scores_codex":[0.9987596,0.00005512302,0.0001945146,0.0004841823,0.0002118031,0.0002947274],"domain_scores_gemma":[0.998368,0.00007031675,0.00004098441,0.001451708,0.00001298484,0.00005605931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001646522,0.0005828779,0.01304738,0.00005427325,0.00004848429,0.00005240367,0.001521699,0.1664142,0.0001127287,0.3062705,0.1046544,0.4072245],"study_design_scores_gemma":[0.0003083906,0.00003449315,0.0007830065,0.00002754278,0.000001190304,0.000003227238,0.00002856167,0.8710843,0.00001737378,0.0003754707,0.1272283,0.0001080734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2039013,0.00004014915,0.7119107,0.002632838,0.001140288,0.0001449135,0.000001030263,0.0004331266,0.07979561],"genre_scores_gemma":[0.97786,0.000001748778,0.01771349,0.0008557598,0.0001510732,0.000001643611,0.00000403228,0.000007372614,0.003404913],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7739586,"threshold_uncertainty_score":0.384668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02115739651338074,"score_gpt":0.2681912636423378,"score_spread":0.2470338671289571,"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."}}