{"id":"W2067801031","doi":"10.1002/cjce.5450790518","title":"Multi‐controller scheme for load rejection and set‐point tracking","year":2001,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Advanced Control Systems Design","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Control theory (sociology); Feed forward; Controller (irrigation); Compensation (psychology); Realizability; Computer science; Load rejection; Scheme (mathematics); Open-loop controller; Set (abstract data type); Tracking (education); Control engineering; Control (management); Engineering; Mathematics; Closed loop; Artificial intelligence; Algorithm","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0003237791,0.0001423662,0.0002378671,0.00009413937,0.0000525091,0.0000550715,0.0001348242,0.0000843528,0.000004621084],"category_scores_gemma":[0.0002809533,0.0001185075,0.00008519647,0.0001016363,0.00002244103,0.0001670759,0.000003666004,0.0002908871,0.000001253528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004524117,"about_ca_system_score_gemma":0.00007391661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001379156,"about_ca_topic_score_gemma":0.0001786124,"domain_scores_codex":[0.9991813,0.000006917237,0.0003138164,0.00007653493,0.0001062818,0.0003152041],"domain_scores_gemma":[0.9993257,0.0001233104,0.00005681397,0.00009061999,0.0001146116,0.0002889613],"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":[0.00004106242,0.000002941552,0.0001153161,0.00007807163,0.0001718325,0.0000355908,0.0005029183,0.2570133,0.7377407,0.0001707083,0.0003510836,0.003776434],"study_design_scores_gemma":[0.002316459,0.00003617898,0.0001377677,0.0001925173,0.00005352634,0.0008877821,0.00003760169,0.9588137,0.02670342,0.0002032718,0.01030714,0.0003106761],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4675442,0.007650465,0.5224879,0.0005399455,0.0009453051,0.0005537307,0.000009829827,0.0001324179,0.0001362097],"genre_scores_gemma":[0.9942536,0.000007618542,0.005244544,0.0000281912,0.0003819222,0.00001082475,3.722914e-7,0.00004170274,0.00003123416],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7110373,"threshold_uncertainty_score":0.4832596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01421967081843441,"score_gpt":0.203926639006039,"score_spread":0.1897069681876045,"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."}}