{"id":"W2893533819","doi":"10.1002/aic.16426","title":"Subsystem decomposition of process networks for simultaneous distributed state estimation and control","year":2018,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Electrochemical Analysis and Applications","field":"Chemistry","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures","keywords":"Modularity (biology); Decomposition; Process (computing); State (computer science); Computer science; Nonlinear system; Control (management); Decomposition method (queueing theory); Process state; Process control; Distributed computing; Control engineering; Mathematical optimization; Engineering; Algorithm; Mathematics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001025668,0.00006863046,0.0001447373,0.00001505528,0.000135208,0.0000330849,0.00006915472,0.00004859055,0.00001845186],"category_scores_gemma":[0.00005691634,0.00005640967,0.00004718089,0.00007659266,0.00004139397,0.00004833398,0.000004913167,0.00009785514,8.217841e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003341434,"about_ca_system_score_gemma":0.00002114314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001890822,"about_ca_topic_score_gemma":0.000003614637,"domain_scores_codex":[0.9994131,0.000007721725,0.0002725071,0.00009157092,0.0000855328,0.000129605],"domain_scores_gemma":[0.9991775,0.0001683885,0.0002484806,0.0000668888,0.0002722805,0.00006651178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004341663,0.0001713969,0.001572298,0.0002520056,0.0003710699,0.000002339332,0.0002084395,0.03442187,0.9449033,0.0001595491,0.0005077217,0.01699587],"study_design_scores_gemma":[0.0005909136,0.00005471455,0.0000388681,0.00005197735,0.0001151368,0.00004765377,0.00002556759,0.8363987,0.1608627,0.001620178,0.0001242852,0.0000693474],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5352842,0.00009306244,0.4643969,0.0001124744,0.000005483489,0.00004319644,0.00002817148,0.000009308986,0.00002724569],"genre_scores_gemma":[0.9990624,0.00001667904,0.0006576552,0.00002354975,0.0001365389,0.00001277297,0.00006025633,0.000006832552,0.00002338082],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8019767,"threshold_uncertainty_score":0.230032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003998936966921269,"score_gpt":0.2674027083796327,"score_spread":0.2634037714127114,"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."}}