{"id":"W4409417760","doi":"10.1016/j.ces.2025.121668","title":"Carbon capture plant model identification through simultaneous state and parameter estimation with estimable variable selection","year":2025,"lang":"en","type":"article","venue":"Chemical Engineering Science","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates","keywords":"Selection (genetic algorithm); Identification (biology); Estimation; Variable (mathematics); Estimation theory; Model selection; Feature selection; Statistics; State variable; Mathematics; Computer science; Econometrics; Engineering; Artificial intelligence; Biology; Thermodynamics; Physics; Botany","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":[0.000103531,0.0001453407,0.000135126,0.00009150188,0.0000572682,0.00009139857,0.0001117552,0.00005647385,4.591523e-7],"category_scores_gemma":[0.0002248755,0.000140167,0.000008091639,0.0006579944,0.00005970058,0.0004091601,0.00001798601,0.0001370742,6.536064e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002083782,"about_ca_system_score_gemma":0.00004460033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001319753,"about_ca_topic_score_gemma":5.91682e-7,"domain_scores_codex":[0.999122,0.000002481106,0.0001828813,0.0002740752,0.0001694172,0.0002491906],"domain_scores_gemma":[0.9996083,0.00008756055,0.00002967382,0.0001463364,0.00007994186,0.00004817143],"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":[0.000004751439,0.000003019413,0.000006803648,0.00006058787,0.000005448941,4.209123e-7,0.00006546289,0.752125,0.2469996,0.0004400425,0.000002968269,0.0002858796],"study_design_scores_gemma":[0.0001621085,0.000004978693,0.000006323496,0.00007410718,0.00001335893,0.000009430452,0.00000305194,0.9106402,0.08824123,0.0006999683,0.000008418322,0.0001367931],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07829921,0.00009501093,0.9208256,0.00001203078,0.00008662824,0.0001801575,0.000004237802,0.0002777808,0.00021932],"genre_scores_gemma":[0.7854595,0.000003642114,0.214396,0.000007999232,0.000006287619,0.00003338902,0.000005603087,0.00001378149,0.00007374991],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7071603,"threshold_uncertainty_score":0.5715846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003203847742777815,"score_gpt":0.1926749673970476,"score_spread":0.1894711196542698,"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."}}