{"id":"W2547256513","doi":"10.1145/2993274.3011285","title":"A model driven method to deploy auto-scaling configuration for cloud services","year":2016,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Cloud computing; Software deployment; Computer science; Vendor; Scaling; Service (business); Distributed computing; Lock (firearm); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002071335,0.00139739,0.0008062791,0.001194103,0.001050054,0.002236729,0.002349583,0.001377496,0.007847037],"category_scores_gemma":[0.004629692,0.001277125,0.001944418,0.0009192104,0.0007746776,0.001616483,0.001965749,0.002237503,0.002109694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001726661,"about_ca_system_score_gemma":0.002836763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009724939,"about_ca_topic_score_gemma":0.01928237,"domain_scores_codex":[0.9987142,0.0003450357,0.00007370864,0.0001958272,0.0005755232,0.00009567112],"domain_scores_gemma":[0.9980725,0.0008936409,0.0001537986,0.0003949772,0.0003845624,0.0001004428],"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":[0.0001535241,0.0003985042,0.001962596,0.0003452302,0.0002132079,0.0005822011,0.0004869308,0.7446406,0.01082235,0.08012216,0.01335031,0.1469224],"study_design_scores_gemma":[0.00002099762,0.00001929436,0.00007073223,0.0000189124,0.00001779773,0.00005252459,0.0000257233,0.9833478,0.001127574,0.01054456,0.00473822,0.00001580471],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001654039,0.00002401239,0.9925618,0.0001097313,0.00003864005,0.000159952,0.00009701461,0.003053197,0.002301661],"genre_scores_gemma":[0.09312774,0.0001056395,0.9008955,0.0001596988,0.00002513864,0.0006049511,0.0005178108,0.0008974503,0.00366602],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009724939,"threshold_uncertainty_score":0.02625096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02505122244221489,"score_gpt":0.2846283781678629,"score_spread":0.259577155725648,"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."}}