{"id":"W2147763077","doi":"10.1109/acc.2005.1470167","title":"Minimum variance benchmark for decentralized controllers","year":2005,"lang":"en","type":"article","venue":"","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Benchmark (surveying); Control theory (sociology); Decentralised system; Variance (accounting); Controller (irrigation); Minimum-variance unbiased estimator; Computer science; Upper and lower bounds; Selection (genetic algorithm); Mathematical optimization; Simple (philosophy); Performance improvement; Control (management); Mathematics; Engineering; Mean squared error; Statistics","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":[0.004409075,0.0009515075,0.001446379,0.00102878,0.0006886908,0.001685754,0.001135349,0.001385489,0.001373682],"category_scores_gemma":[0.02251953,0.000252519,0.0004493377,0.0007374401,0.0008045397,0.001709006,0.001362558,0.001291741,0.000385342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008326287,"about_ca_system_score_gemma":0.0008930545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006309469,"about_ca_topic_score_gemma":0.0004473427,"domain_scores_codex":[0.9939755,0.002251731,0.0002421145,0.0006629861,0.00234517,0.0005226014],"domain_scores_gemma":[0.9886016,0.006945704,0.001130746,0.001269236,0.001818113,0.0002345622],"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":[0.0005531214,0.0001453649,0.00124493,0.0002192139,0.0000655726,0.0001031427,0.00006360748,0.8734127,0.01960934,0.05646636,0.001501907,0.04661485],"study_design_scores_gemma":[0.00002785218,0.0003616578,0.0005523801,0.00002837871,0.000009301858,0.00004777229,0.00001973266,0.9654908,0.009474003,0.02329233,0.000674205,0.00002155176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07190742,0.0007140694,0.9165796,0.0002440641,0.00006838745,0.00006827334,0.000138914,0.0006827689,0.009596528],"genre_scores_gemma":[0.9486279,0.0001441263,0.04971936,0.00007878904,0.00005498064,0.0001239539,0.0002318914,0.0001094727,0.0009095487],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004409075,"threshold_uncertainty_score":0.02331769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006622410090932947,"score_gpt":0.2153100598656255,"score_spread":0.2086876497746926,"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."}}