{"id":"W4413967213","doi":"10.1109/tcc.2025.3605828","title":"Ksurf+: Attention Kalman Filter for Prediction Under Highly Variable Cloud Workloads","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Cloud Computing","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Cloud computing; Kalman filter; Computer science; Variable (mathematics); Artificial intelligence; Operating system; Mathematics","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":[0.001154681,0.001095949,0.001029635,0.0005028248,0.000521865,0.0007646657,0.001218315,0.001012094,0.003723657],"category_scores_gemma":[0.004698192,0.0004489075,0.0006317914,0.0005770086,0.0003444377,0.001170682,0.0008464541,0.001647571,0.001358578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000879171,"about_ca_system_score_gemma":0.001729917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04011685,"about_ca_topic_score_gemma":0.03242144,"domain_scores_codex":[0.9994822,0.000110266,0.00003984995,0.0001297077,0.000172507,0.00006554739],"domain_scores_gemma":[0.9988058,0.0006602996,0.00008797683,0.000111954,0.0002984625,0.0000354418],"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":[0.0003759204,0.00009104539,0.002245924,0.0001839943,0.0001250768,0.0001027521,0.0001110291,0.6799076,0.004769564,0.006552887,0.0096068,0.2959273],"study_design_scores_gemma":[0.000007158009,0.00001149756,0.0001900158,0.000005189585,0.000004591566,0.000005741751,0.00000388347,0.9974502,0.0008215649,0.0008685517,0.0006257304,0.000005823256],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007902632,0.0003788349,0.9853337,0.0001715192,0.0001001834,0.00003893145,0.0002234457,0.004739283,0.001111413],"genre_scores_gemma":[0.5813958,0.00078732,0.4074234,0.0003571623,0.0002157096,0.0003116122,0.001732306,0.000722362,0.007054308],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04011685,"threshold_uncertainty_score":0.07976669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01615788517970396,"score_gpt":0.2458744044375923,"score_spread":0.2297165192578884,"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."}}