{"id":"W2996626254","doi":"10.1002/acs.3074","title":"Distributed monitoring of the absorption column of a post‐combustion CO<sub>2</sub> capture plant","year":2019,"lang":"en","type":"article","venue":"International Journal of Adaptive Control and Signal Processing","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; Killam Trusts","keywords":"Estimator; Column (typography); Combustion; Fault (geology); State (computer science); Work (physics); Absorption (acoustics); Computer science; Distributed computing; Environmental science; Engineering; Chemistry; Mathematics; Materials science; Algorithm; Geology; Telecommunications; Mechanical engineering; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001727041,0.0002729914,0.0002891441,0.0001210029,0.0003425311,0.000275319,0.000426741,0.0003709072,0.0003923037],"category_scores_gemma":[0.0003327296,0.0001154527,0.0001366213,0.0001128612,0.0003169834,0.0003483602,0.0003171261,0.0003845723,0.00004243537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005056941,"about_ca_system_score_gemma":0.0004950471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005941306,"about_ca_topic_score_gemma":0.006044035,"domain_scores_codex":[0.9998759,0.00001996371,0.000002429261,0.00004461634,0.00003987926,0.00001723118],"domain_scores_gemma":[0.9997365,0.0001131884,0.00004959514,0.00002002394,0.00005964707,0.00002108998],"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":[0.00053373,0.0001290087,0.008889236,0.0000634625,0.00004326991,0.0004094051,0.00009628198,0.8287973,0.120372,0.001193398,0.0004814182,0.0389915],"study_design_scores_gemma":[0.00001421618,0.00009536342,0.003749264,0.000001876532,0.000008558391,0.00003816671,0.00002834581,0.9830309,0.01246165,0.0004218409,0.0001433561,0.00000642736],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7273843,0.0001314532,0.2695855,0.0002418091,0.00001978562,0.00003957073,0.00006697706,0.0003155617,0.00221507],"genre_scores_gemma":[0.9972984,0.00001028614,0.002394831,0.00000730888,0.000003028919,0.000004859579,0.000009374822,0.000001633749,0.0002702128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005941306,"threshold_uncertainty_score":0.01181346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005554083269617777,"score_gpt":0.2027641917515102,"score_spread":0.1972101084818924,"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."}}