{"id":"W4415746452","doi":"10.1016/j.ces.2025.122891","title":"Efficient state estimation for post-combustion CO2 capture plants using PODAE-based reduced-order modeling","year":2025,"lang":"en","type":"article","venue":"Chemical Engineering Science","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China","keywords":"Extended Kalman filter; Autoencoder; Nonlinear system; Process (computing); Artificial neural network; Dimensionality reduction; Multilayer perceptron; Kalman filter; Curse of dimensionality; Computational complexity theory","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002257087,0.0002113678,0.0001884732,0.000369492,0.00004647005,0.00007049272,0.0003436426,0.0001241987,9.656436e-7],"category_scores_gemma":[0.0006600661,0.000222884,0.00005137156,0.0008641105,0.0001005519,0.00008936175,0.000052801,0.0002292553,0.000001104195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004898374,"about_ca_system_score_gemma":0.0001260844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008054511,"about_ca_topic_score_gemma":1.961922e-7,"domain_scores_codex":[0.998743,0.00000196326,0.0002420645,0.000328916,0.0002400064,0.0004440453],"domain_scores_gemma":[0.9993837,0.00007357867,0.00002396441,0.0002861184,0.0001630345,0.00006959197],"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":[0.000003831899,0.000004411792,8.697195e-7,0.00006731489,0.000002957583,4.581536e-7,0.00001994845,0.5336257,0.465938,0.00008533359,0.000006003792,0.0002452455],"study_design_scores_gemma":[0.0001514972,0.000003072002,0.000005529749,0.0001151639,0.000007656959,0.000002299257,0.00001454342,0.615996,0.383501,0.00005957388,0.000002848297,0.0001408156],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5353352,0.0001137388,0.4633636,0.00004392993,0.0002758517,0.0001607122,0.00001044852,0.0006795065,0.00001694919],"genre_scores_gemma":[0.9328696,0.000001075481,0.06702076,0.00002681663,0.00001239211,0.0000310737,0.00001063298,0.00002425483,0.000003451311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3975343,"threshold_uncertainty_score":0.9088947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008961016628553982,"score_gpt":0.2292860667496475,"score_spread":0.2203250501210935,"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."}}