{"id":"W3189639319","doi":"10.1016/j.mechatronics.2021.102633","title":"Data-driven fault tolerant predictive control for temperature regulation in data center with rack-based cooling architecture","year":2021,"lang":"en","type":"article","venue":"Mechatronics","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Rack; Model predictive control; Controller (irrigation); Actuator; Data center; Control theory (sociology); Engineering; Fault (geology); Control engineering; Fuzzy logic; Nonlinear system; Temperature control; Computer science; Control (management); Artificial intelligence","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":[0.0001829967,0.0002081616,0.000307222,0.00007097851,0.00005797997,0.00005873614,0.0003787367,0.0001375456,0.000007100944],"category_scores_gemma":[0.00008506195,0.0001916122,0.00002573106,0.0001904003,0.00001270472,0.0003842454,0.00006211099,0.0002690898,0.000001320544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001587896,"about_ca_system_score_gemma":0.0001165832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002685513,"about_ca_topic_score_gemma":0.0004582011,"domain_scores_codex":[0.998648,0.00005916612,0.0003022519,0.000481982,0.0001957874,0.0003127502],"domain_scores_gemma":[0.9984561,0.0001098563,0.00007495367,0.001174192,0.0001351569,0.00004975469],"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":[0.0002495143,0.00002395668,0.0000744104,0.00009131605,0.00007030804,0.000006685752,0.00006833742,0.9952633,0.003196166,0.0001235384,0.000180699,0.0006517611],"study_design_scores_gemma":[0.004501552,0.00003631712,0.00005181205,0.0001779192,0.00004895621,0.000008279321,0.00005866935,0.9889011,0.0005630518,0.00006010444,0.005392005,0.0002002205],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002611905,0.0006654953,0.9917629,0.0002435853,0.0002118479,0.0009026839,0.003407656,0.0001732147,0.00002073047],"genre_scores_gemma":[0.9390595,0.00001486575,0.05027013,0.0000887871,0.0001866393,0.00009205586,0.01018765,0.00007561094,0.0000247964],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9414927,"threshold_uncertainty_score":0.7813718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01168175006751579,"score_gpt":0.2298385520693863,"score_spread":0.2181568020018705,"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."}}